statewide waste characterization study

California Integrated Waste Management Board

Statewide Waste Characterization Study

Results and Final Report

prepared by Cascadia Consulting Group, Inc. Sky Valley Associates, Inc. Sheri Eiker-Wiles Associates Pacific Waste Consulting Group Veterans Assistance Network E. Tseng and Associates E. Ashley Steel

in cooperation with California Integrated Waste Management Board staff

December 1999

STATE OF CALIFORNIA Gray Davis Governor

Winston Hickox

Secretary, California Environmental Protection Agency

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INTEGRATED WASTE MANAGEMENT BOARD Dan Eaton

Board Chairman

Steven R. Jones Board Member

Linda Moulton-Patterson Board Member

Daniel G. Pennington Board Member

David A. Roberti Board Member

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Ralph E. Chandler Executive Director

For additional copies of this publication, contact:

Integrated Waste Management Board

Public Affairs Office 8800 Cal Center Drive, MS 12

Sacramento, CA 95826

www.ciwmb.ca.gov/Publications/ (800) CA-WASTE (California only) or (916) 255-2296

Publication #340-00-009

Printed on Recycled Paper

Copyright 1999 by the Integrated Waste Management Board. All rights reserved. This publication, or parts thereof, may not be reproduced in any form without permission.

The statements and conclusions of this report are those of the contractor and not necessarily those of

the California Integrated Waste Management Board, its employees, or the State of California. The State makes no warranty, expressed or implied, and assumes no liability for the information contained in the succeeding text. Any mention of commercial products or processes shall not be

construed as an endorsement of such products or processes.

Prepared under contract number IWM-C8014 ($635,700).

The Integrated Waste Management Board (IWMB) does not discriminate on the basis of disability in access to its programs. IWMB publications are available in accessible formats upon request by calling the Public Affairs Office at (916) 255-2296. Persons with hearing impairments can reach

the IWMB through the California Relay Service, 1-800-735-2929.

This study would not have been possible without the cooperation and assistance of solid waste management companies, disposal sites, waste haulers, and commercial enterprises throughout

the State of California.

Table of Contents

1. Executive Summary ES - 1 1.1 Introduction and Objectives ES - 1 1.2 Study Methodology ES - 1 1.3 Results ES - 2

2. Introduction and Overview 1 2.1 Objectives of the Study 1 2.2 Contributing Consultants 1 2.3 Preparation for Sampling 2 2.4 Waste Sectors 2 2.5 Dividing the State Into Regions 3 2.6 Selection of Sites 5 2.7 Capture and Sorting of Waste Samples 5

2.7.1 Commercial Generator Samples 7 2.7.2 Residential Samples 7 2.7.3 Self-Haul Samples 8

2.8 Vehicle Surveys 8 3. Results 8

3.1 Composition of California’s Overall Waste Stream 8 3.2 Statewide Tonnages by Sector 12

3.2.1 Vehicle Survey 12 3.2.2 Statewide Percentages and Tonnages by Sector 13 3.2.3 Commercial Self-haul Activities 14

3.3 Commercial Waste 14 3.3.1 The Overall Commercial Sector 14 3.3.2 Composition by Industry Group 22

3.4 Residential Waste 50 3.4.1 The Overall Residential Sector 50 3.4.2 Single-Family Residential Waste 53 3.4.3 Multifamily Residential Waste 57

3.5 Self-haul Waste 60 3.5.1 The Overall Self-Haul Sector 60 3.5.2 Commercial Self-Haul Waste 64 3.5.3 Residential Self-Haul Waste 67

3.6 RPPC Study 70

3.6.1 Introduction and Background 70 3.6.2 Methodology 71 3.6.3 Results 72

Appendix A: Detailed Methodology A - 1 A.1 Introduction A - 1 A.2 Selection of Regions, Disposal Sites & Waste Sheds A - 1

A.2.1 Selection of Regions A - 2 A.2.2 Selection of Sites A - 6 A.2.3 Communications Plan A - 11

A.3 Discussion of Numbers of Samples A - 11 A.4 Generator Selection and Capture Procedures A - 13

A.4.1 Commercial Generator Samples A - 13 A.4.2 Multifamily Residential Samples A - 19 A.4.3 Volume and Density Measurements for Generator Samples A - 21

A.5 Disposal Site Sample Selection A - 22 A.5.1 Single-Family Residential Waste A - 22 A.5.2 Residential Self-haul and Commercial Self-haul Waste A - 22

A.6 Sample Sorting and Data Recording A - 23 A.6.1 Waste Sorting Procedures A - 23 A.6.2 Health and Safety Protection A - 24

A.7 Vehicle Survey A - 25 A.7.1 Survey Approach A - 25

A.8 Base Population and Disposal Data A - 26 A.8.1 Annual Tonnage Estimates for Each Region and Statewide A - 26 A.8.2 Number of Apartments in Each Region and Statewide A - 27

A.9 Quality Control Procedures A - 27 A.9.1 Identification of Commercial and Multi-Family Generators A - 27 A.9.2 Vehicle Surveys A - 28 A.9.3 Waste Sampling A - 28

A.10 Description of statistical procedures used A - 29 A.10.1 Vehicle surveys A - 29 A.10.2 Calculating composition percentages from samples A - 33 A.10.3 Calculating tons per employee per year (TPEPY) A - 38 A.10.4 Calculating average volume and average density by industry group A - 41 A.10.5 Variance calculations A - 41 A.10.5 RPPC study A - 43

Appendix B: List and Definitions of Material Types B - 1 B.1 List of Standard Material Categories B - 1 B.2 Definitions of Standard Material Categories B - 3

Paper B - 3 Glass B - 4 Metal B - 5 Plastic B - 6 Other Organic B - 7

Construction And Demolition B - 9 Household Hazardous Waste B - 9 Special Waste B - 10 Mixed Residue B - 11

B.3 List and Examples of RPPCs B - 12 Appendix C: CIWMB Standard Method C - 1

C.1 Draft Regulations Governing Disposal Characterization Studies C - 1 C.2 Guidelines Governing Health and Safety Measures C - 21 C.3 Guidelines Governing Solid Waste Sorting Procedures C - 28

Appendix D: Forms Used in the Study D - 1 Form Used for Vehicle Surveys D - 1 Snapshot of Generator Recruitment Database D - 2 Snapshots of Database for Entry of Component Weights in the Field D - 3

Appendix E: Definitions of Business Groups E - 1 Appendix F: Distribution of Employment by Business Group and Region F - 1 Appendix G: Numbers of Samples by Sector, Site, Region, and Season G - 1

Disposal Site Samples G - 1 Generator Samples G - 2

Appendix H: Numbers of Vehicles Surveyed by Site, Region, and Season H - 1 Appendix I: Paper on Calculating RPPC Contamination Rates I - 1 Appendix J: County Demographic Data Used in Selection of Regions J - 1 Appendix K: Questions Used to Determine Suitability of Sorting Sites K - 1 Appendix L: Data Elements of the Study L - 1

Table of Tables

Table ES - 1: Estimated Contribution of Each Sector to the Overall Waste Stream ES - 2 Table ES - 2: Top 10 Materials in the Overall Waste Stream ES - 3 Table ES - 3: Composition of the Overall Waste Stream by Material Type ES - 5

Table 1: Overview of Consultants’ Responsibilities 2 Table 2: Overview of Waste Disposal Sectors and Subsectors 3 Table 3: Numbers of Samples Collected from Each Sector 6 Table 4: Most Prevalent Materials in the Overall Waste Stream 10 Table 5: Composition of Overall Waste Stream 11 Table 6: Numbers of Vehicles Surveyed by Region and Season 12 Table 7: Statewide Tonnage and Percentage of Waste Stream by Sector 13 Table 8: Annual Residential Disposed Waste Per-Capita for Each Region 13 Table 9: Contribution of Specific Activities to the Commercial Self-Haul Subsector 14 Table 10: Numbers of Commercial Samples Collected by Industry Group and Region 15 Table 11: Distribution of the Number of Employees at Commercial Sites that were Sampled 16 Table 12: Annual Disposal Volume and Waste Density by Industry Group 17 Table 13: Per-Employee Disposal Rate and Estimated Contribution of Each Industry Group to

Commercial Waste 18 Table 14: Relative Contribution of Each Industry Group to Commercial Waste 19 Table 15: Most Prevalent Materials in Commercial Waste 20 Table 16: Composition of Commercial Waste 21 Table 17: Composition of Waste from Group A: Finance / Insurance / Real Estate / Legal 24 Table 18: Composition of Waste from Group B: Retail Trade - Restaurants 25 Table 19: Composition of Waste from Group C: Retail Trade - Other 26 Table 20: Composition of Waste from Group D: Services - Other Misc. 27 Table 21: Composition of Waste from Group E: Wholesale Trade - Nondurable Goods 28 Table 22: Composition of Waste from Group F: Retail Trade - Automotive Dealers & Service Stations 29 Table 23: Composition of Waste from Group G: Services - Other Professional 30 Table 24: Composition of Waste from Group H: Retail Trade - Food Store 31 Table 25: Composition of Waste from Group I: Construction 32 Table 26: Composition of Waste from Group J: Services - Medical / Health 33 Table 27: Composition of Waste from Group K: Manufacturing - Printing / Publishing 34 Table 28: Composition of Waste from Group L: Services - Business Services 35 Table 29: Composition of Waste from Group M: Services - Education 36 Table 30: Composition of Waste from Group N: Public Administration 37 Table 31: Composition of Waste from Group O: Services - Hotels / Lodging 38 Table 32: Composition of Waste from Group P: Trucking & Warehousing 39 Table 33: Composition of Waste from Group Q: Wholesale Trade - Durable Goods 40

Table 34: Composition of Waste from Group R: Manufacturing - Other 41 Table 35: Composition of Waste from Group S: Transportation - Other 42 Table 36: Composition of Waste from Group T: Manufacturing - Electronic Equipment 43 Table 37: Composition of Waste from Group U: Manufacturing - Food / Kindred 44 Table 38: Composition of Waste from Group V: Manufacturing - Lumber & Wood Products 45 Table 39: Composition of Waste from Group W: Manufacturing - Transportation Equipment 46 Table 40: Composition of Waste from Group X: Retail Trade - Building Material & Garden 47 Table 41: Composition of Waste from Group Y: Manufacturing - Industrial / Machinery 48 Table 42: Composition of Waste from Groups Z through AM: Lumped Group 49 Table 43: Most Prevalent Materials in Overall Residential Waste 51 Table 44: Composition of Overall Residential Waste 52 Table 45: Single-Family Residential Samples Obtained, by Region and Season 53 Table 46: Most Prevalent Materials in Single-Family Residential Waste 55 Table 47: Composition of Single-Family Residential Waste 56 Table 48: Multifamily Residential Samples Obtained, by Region and Season 57 Table 49: Most Prevalent Materials in Multifamily Residential Waste 58 Table 50: Composition of Multifamily Residential Waste 59 Table 51: Self-Haul Samples Obtained, by Region and Season 60 Table 52: Most Prevalent Materials in Overall Self-Haul Waste 62 Table 53: Composition of Overall Self-Haul Waste 63 Table 54: Commercial Self-Haul Samples Obtained, by Region and Season 64 Table 55: Most Prevalent Materials in Commercial Self-Haul Waste 65 Table 56: Composition of Commercial Self-Haul Waste 66 Table 57: Residential Self-Haul Samples Obtained, by Region and Season 67 Table 58: Most Prevalent Materials in Residential Self-Haul Waste 68 Table 59: Composition of Residential Self-Haul Waste 69 Table 60: Field Weight to Clean Weight Conversion Factors for RPPCs 71 Table 61: RPPC Composition of Overall Waste Stream 73 Table 62: RPPC Composition for Commercial Waste 73 Table 63: RPPC Composition in Residential Waste 74 Table 64: RPPC Composition in Self-Haul Waste 74

Table 65: Counties in the Five Sampling Regions A - 4 Table 66: Primary Factors for Selection of Sampling Regions A - 5 Table 67: Secondary Factors for Selection of Sampling Regions A - 5 Table 68: Suitable Sampling Sites in Each Region A - 7 Table 69: Selected Sampling Sites A - 8 Table 70: Sorting Site Characteristics A - 9 Table 71: Sorting Sites, Seasons, and Locations A - 10 Table 72: Numbers of Samples Collected from Each Sector A - 12 Table 73: Targeted Distribution of Commercial Samples, Based on Regional Employment A - 14 Table 74: Commercial Samples Collected by Region, Winter Season A - 17 Table 75: Commercial Samples Collected by Region, Summer Season A - 18

Table 76: Total Waste Disposal (Tons) in Each County and Region, 1998 A - 26 Table 77: Numbers of Multifamily Units by County and Region, 1998 A - 27 Table 78: Description of Industry Groups Designated in the Study E - 1 Table 79: Numbers of Employees by Industry Group in Each Region F - 1 Table 80: Numbers of Businesses by Industry Group in Each Region F - 2

Table of Figures

Figure ES - 1: Material Classes in the Overall Waste Stream ES - 4 Figure ES - 2: Material Classes in the Commercial Waste Stream ES - 4 Figure ES - 3: Material Classes in the Residential Waste Stream ES - 4 Figure ES - 4: Material Classes in the Self-Haul Waste Stream ES - 4

Figure 1: Regions Used in the Study 4 Figure 2: Overview of Overall Waste Stream 9 Figure 3: Overview of Commercial Waste 20 Figure 4: Overview of Overall Residential Waste 51 Figure 5: Overview of Single-Family Residential Waste 54 Figure 6: Overview of Multifamily Residential Waste 58 Figure 7: Overview of Overall Self-Haul Waste 61 Figure 8: Overview of Commercial Self-Haul Waste 65 Figure 9: Overview of Residential Self-Haul Waste 68

Figure 10: Regions Considered in the Study A - 3 Figure 11: Translation of Field Sorting Categories to Study Categories of Plastics A - 24

1. EXECUTIVE SUMMARY

1.1 INTRODUCTION AND OBJECTIVES

During 1999 the California Integrated Waste Management Board (CIWMB) conducted a statewide study whose primary objective was to obtain information on the types and amounts of materials still being disposed in the state. The first such study of this magnitude, it encompassed gathering data from the commercial, residential, and self-haul waste streams throughout California. No information was gathered on materials diverted from disposal through source reduction, recycling, or composting. The standard methods contained in the California Uniform Waste Disposal Characterization Method were used. In addition, the study was designed to determine a defensible estimate of the amount of Rigid Plastic Packaging Containers (RPPCs) disposed in California. This information is needed to calculate the recycling rate for RPPCs, which is required by state law. Also, data was gathered on the types and quantities of commercial waste disposed by 26 different types of businesses and institutions. This data will be added to the CIWMB Waste Characterization Database to serve as a resource to local governments.

1.2 STUDY METHODOLOGY

For study purposes, the waste stream was divided into three sectors: residential, commercial, and self-haul. The residential sector was further sub-divided into single and multifamily subsectors, and the self-haul into residential and commercial subsectors. The state was divided into five regions based on similarity of demographics and geographic features. A statistically-derived number of samples was allocated to each region to ensure adequate representation. In each region, five disposal sites (landfills and transfer stations) were randomly selected as sampling sites for the single family residential and self-haul waste streams. Collections at these sites totaled 148 single family residential and 247 self-haul samples. A total of 1207 commercial generator and 80 multifamily residential samples were collected from randomly selected businesses and apartment complexes within the geographical areas surrounding the selected disposal sites. Waste sampling was divided between winter and summer to account for any seasonal variations in waste disposal patterns. Each sample was hand sorted and characterized using the 57 material types found in the California Uniform Waste Disposal Characterization Method, as well as eight specific RPPC categories identified for this study. Additionally, vehicle surveys were used to estimate the portion of California’s waste contributed by each of the residential, commercial, and self-haul sectors. The surveys were conducted at 24 of the 25 sites that were visited for disposal site sampling, and on the same days that sampling occurred. All vehicles bringing waste to the site during a pre-determined eight-hour period were surveyed. The generating sector represented by the waste was identified, and the net weight of each load was recorded. A total of 3,648 surveys were completed.

California 1999 Statewide ES - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

1.3 RESULTS

The data gathered during the sampling efforts was reduced and statistical analyses were performed in order to extrapolate the findings to statewide estimates. The Final Report includes detailed findings for the following areas:

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Disposed waste composition and tonnage for the state's overall waste stream and the commercial, residential, and self-haul sectors;

Disposed waste composition and tonnage for 26 industry groups;

Disposed waste composition and tonnage of both single-family and multi-family subsectors;

Disposed waste composition and tonnage of commercial self-haul and residential self-haul subsectors;

Disposed waste composition and tonnage for RPPCs. The findings show that, statewide, the commercial sector comprises 48.8% of the waste stream, the residential sector (single-family plus multifamily) represents 38.1%, and the self-haul sector is responsible for the remaining 13.1 percent. The data also show that 377,010 tons of RPPCs are being disposed statewide, equating to 1.06% of the overall waste stream. Table ES - 1 depicts the estimated contribution to the overall waste stream of each sector. Figures ES - 1 through ES - 4 display the breakdown of the waste stream by nine major categories in the overall, as well as each of the main sectors sampled. Finally, Table ES - 2 lists the ten most prevalent materials in the overall waste stream, which account for nearly 65% of California’s disposed waste, while Table ES - 3 provides a complete breakdown of the composition of the overall waste stream by material type.

Table ES - 1: Estimated Contribution of Each Sector to the Overall Disposed Waste Stream

Est. Percent of Waste Stream

Est. Tons Statewide

Commercial 48.8% 17,358,359

Residential 38.1% 13,525,504 Single-family residential 28.0% 9,955,739 Multifamily residential 10.0% 3,569,888

Self-haul 13.1% 4,651,591 Commercial self-haul 10.5% 3,739,696 Residential self-haul 2.6% 911,770

Totals 100.0% 35,535,453 Source: 1999 vehicle survey findings applied to CIWMB Disposal Reporting System 1998 tonnage figures.


Table ES - 2: Top 10 Materials in the Overall Disposed Waste Stream

Material Type Est. Pct. Est. Tons Cumulative Pct. Food 15.7% 5,584,506 15.7% Remainder/Composite Paper 9.6% 3,416,281 25.3% Leaves & Grass 7.9% 2,808,692 33.2% Remainder/Composite Organic 6.9% 2,453,912 40.1% Lumber 4.9% 1,746,001 45.1% Uncoated Corrugated Cardboard 4.6% 1,630,348 49.6% Other Miscellaneous Paper 4.4% 1,565,454 54.0% Newspaper 4.3% 1,521,186 58.3% Film Plastic 3.9% 1,377,438 62.2% Other Ferrous Metal 2.4% 866,716 64.6%

Any differences between cumulative percent figures and the sum of estimated percent figures are due to rounding.


Califor CascaWaste Composition Study California Integ

nia 1999 Statewide ES - 4 dia Consulting Group, Inc., for the rated Waste Management Board

Figure ES - 1: Material Classes in the Overall Disposed Waste Stream

Construction &

Demolition 11.6%

Household Hazardous

0.3%

OtherOrganic35.1%

Paper30.2%

Mixed Residue 1.8%

Special 3.1%

Plastic 8.9%

*

Metal6.1%

Glass2.8%

Figure ES - 2: Material Classes in the Commercial Disposed Waste Stream

Construction &Demolition

6.4%

Special4.1%

HouseholdHazardous

0.3%

Plastic9.8%

OtherOrganic31.3%

Paper39.0%

Mixed Residue0.5%

Metal6.0%

Glass2.4%

Figure ES - 3: Material Classes in the Residential Disposed Waste Stream


4.5%

Special1.2%

Household Hazardous0.3%

Plastic8.8%

OtherOrganic45.0%

Metal4.6%

Glass4.0%

Paper27.4%

Mixed Residue4.0%

Figure ES - 4: Material Classes in the Self-Haul Disposed Waste Stream


51.3%

Special4.9%

Household Hazardous0.1%

Plastic5.6%

OtherOrganic20.8%

Metal10.6%

Glass1.0%

Paper5.5%

Mixed Residue0.2%

* The class Other Organic Waste includes materials such as food, yard waste, textiles, carpet, and rubber.


Est. Pct. + / - Est. Tons Est. Pct. + / - Est. Tons

Paper 30.2% 10,742,707 Other Organic 35.1% 12,490,171Uncoated Corrugated Cardboard 4.6% 0.2% 1,630,348 Food 15.7% 0.6% 5,584,506Paper Bags 0.7% 0.0% 261,563 Leaves & Grass 7.9% 0.7% 2,808,692Newspaper 4.3% 0.3% 1,521,186 Prunings & Trimmings 2.2% 0.4% 790,727White Ledger Paper 2.3% 0.2% 812,752 Branches & Stumps 0.1% 0.1% 52,940Colored Ledger Paper 0.2% 0.0% 60,270 Agricultural Crop Residues 0.0% 0.0% 1,765Computer Paper 0.3% 0.1% 114,545 Manures 0.1% 0.1% 49,291Other Office Paper 1.7% 0.2% 591,080 Textiles 2.1% 0.3% 748,336Magazines and Catalogs 1.9% 0.1% 669,434 Remainder/Composite Organic 6.9% 0.5% 2,453,912Phone Books and Directories 0.3% 0.1% 99,793Other Miscellaneous Paper 4.4% 0.2% 1,565,454 Construction & Demolition 11.6% 4,110,526Remainder/Composite Paper 9.6% 0.4% 3,416,281 Concrete 1.2% 0.2% 418,600

Asphalt Paving 0.1% 0.1% 49,614Glass 2.8% 1,011,441 Asphalt Roofing 0.7% 0.2% 252,254

Clear Glass Bottles & Containers 1.4% 0.1% 506,214 Lumber 4.9% 0.5% 1,746,001Green Glass Bottles & Containers 0.4% 0.1% 154,191 Gypsum Board 1.1% 0.2% 402,784Brown Glass Bottles & Containers 0.5% 0.0% 167,529 Rock, Soil & Fines 1.3% 0.3% 461,437Other Colored Glass Bottles & Containers 0.0% 0.0% 6,859 Remainder/Composite C&D 2.2% 0.3% 779,836Flat Glass 0.1% 0.0% 23,206Remainer/Composite Glass 0.4% 0.1% 153,443 Household Hazardous Waste 0.3% 106,497

Paint 0.1% 0.0% 42,167Metal 6.1% 2,164,080 Vehicle & Equipment Fluids 0.0% 0.0% 13,596

Tin/Steel Cans 1.0% 0.1% 339,570 Used Oil 0.0% 0.0% 1,579Major Appliances 0.1% 0.0% 23,257 Batteries 0.1% 0.0% 30,929Other Ferrous Metal 2.4% 0.3% 866,716 Remainder/Composite HHW 0.1% 0.0% 18,226Aluminum Cans 0.2% 0.0% 87,086Other Non-Ferrous Metal 0.3% 0.0% 93,548 Special Waste 3.1% 1,110,383Remainder/Composite Metal 2.1% 0.3% 753,903 Ash 0.1% 0.0% 21,464

Sewage Solids 0.0% 0.0% 0Plastic 8.9% 3,161,711 Industrial Sludge 0.0% 0.0% 18

HDPE Containers 0.8% 0.0% 275,944 Treated Medical Waste 0.0% 0.0% 6,478PETE Containers 0.5% 0.0% 160,615 Bulky Items 1.8% 0.6% 656,509Miscellaneous Plastic Containers 0.7% 0.1% 239,954 Tires 0.4% 0.2% 145,899Film Plastic 3.9% 0.2% 1,377,438 Remainder/Composite Special Waste 0.8% 0.3% 280,017Durable Plastic Items 1.8% 0.2% 631,536Remainder/Composite Plastic 1.3% 0.1% 476,224 Mixed Residue 1.8% 0.2% 637,938

Sample count: 1,682 Totals 100.0% 35,535,453Confidence intervals calculated at the 90% confidence level. Percentages for materials may not total 100% due to rounding.

Table ES - 3: Composition of the Overall Disposed Waste Stream by Material Type

2. INTRODUCTION AND OVERVIEW

The California Integrated Waste Management Board (CIWMB) commissioned a Statewide Waste Disposal Characterization Study in order to obtain data to characterize the residential, commercial, and self-haul waste streams. Information on the types and amounts of materials disposed in these waste streams was gathered through sampling of the waste delivered to disposal sites and waste collected directly from commercial generators (individual businesses) and apartment buildings. This study did not gather information on materials diverted through source reduction, recycling, or composting. The Study provides detailed information on the composition of waste disposed in California during 1999. The design for the Study was prepared by a team of consultants led by the Cascadia Consulting Group, under the direction of CIWMB staff. In addition, an Advisory Group appointed by the CIWMB reviewed and approved the design. A study like this is challenging because it seeks to apply pure statistical methods within the real-world limitations imposed by budgeting and time considerations, the day-to-day operations of solid waste transfer and disposal sites, and business operations. This study sought to find the proper balance – a statistically valid analysis that was cost-effective and a process for gathering data that was not disruptive to facility operators or their customers, or individual businesses.

2.1 OBJECTIVES OF THE STUDY

The primary objective of this project was to characterize California’s municipal solid waste using the standard methods contained in the California Uniform Waste Disposal Characterization Method. These standard methods include statistically reliable methods to determine sample sizes, categories of waste to be measured, analytical techniques, field procedures, and other methodologies. These standard methods were the basis for many of the decisions made in the project design. In addition, there were two secondary project objectives. First, the state wanted to determine a defensible estimate of the amount of Rigid Plastic Packaging Containers (RPPCs) disposed in California. This is needed to calculate the recycling rate for RPPCs, which is required by state law. Second, data was gathered on the type and quantity of commercial waste disposed by numerous categories of commercial generators. These data will be added to the CIWMB Waste Characterization database to serve as a resource to local governments.

2.2 CONTRIBUTING CONSULTANTS

The Cascadia Consulting Group, Inc., a Seattle-based environmental consulting firm, was the prime contractor and manager of this Study. The roles of Cascadia and the other consultants are described briefly in Table 1.

California 1999 Statewide 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

Table 1: Overview of Consultants’ Responsibilities

Consultant Overview of Major Responsibilities Cascadia Consulting Group, Inc. Project management, study design, data management

and analysis, reporting Sky Valley Associates, Inc. (SVA) Conduct waste sampling Sheri Eiker-Wiles Associates (SEWA) Select & survey commercial waste generators E. Tseng and Associates Technical advice and review E. Ashley Steel Provide advice on developing statistically valid sampling

procedures; assist in analysis Pacific Waste Consulting Group (PWCG)

Assist with site selection plan; conduct vehicle surveys

Veterans Assistance Network (VAN) Verify data on selected commercial generators; enter data from waste sampling and vehicle surveys

2.3 PREPARATION FOR SAMPLING

Planning for a comprehensive waste characterization study requires careful consideration of many factors. This study was designed to ensure representative data from across the state of California, as well as to gather data that will be useful for analyses by local governments. To accomplish this, the project used a stratified random sampling methodology. Waste was sampled from numerous subgroups (strata) to develop a waste composition profile for each stratum. Then the data were aggregated in a way that reflects each stratum’s relative contribution to the overall waste stream, thus producing overall waste composition information. Strata considered in this study include the geographical region, the waste sector (residential, commercial or self-haul), the activity that generated the waste, the type of business or institution that generated the waste, and the size of business or institution that generated the waste.

2.4 WASTE SECTORS

Waste was characterized for three sectors: residential waste, commercial waste, and self-haul waste. Within each sector, waste was divided into sub-sectors, as shown in Table 2.


Table 2: Overview of Waste Disposal Sectors and Subsectors

Commercial Waste

26 industry groups

Residential Waste

Single-Family Residential

Multifamily Residential

Self-Haul Waste

Residential Self-Haul

Commercial Self-Haul

Roofing

Landscaping

Construction/Demolition

Other

Waste disposed by businesses, industries, and publicorganizations that is collected and transported byprofessional waste haulers

Waste disposed by specific industry groups, based on SICcodes. (See appendix E.)

Waste disposed by households that is collected andtransported by professional waste haulers

Waste that is collected from single-family residences

Waste that is collected from apartments or condominiums

Waste that is transported to the disposal site by someonewhose primary business is NOT waste hauling

Waste hauled to a disposal site by a resident from their home

Waste hauled to a disposal site by a commercial enterprise (e.g.landscaper, contractor, etc.), even if source of waste was fromresidential dwellings. Commercial self-haul was further brokendown into four types: roofing, landscaping,construction/demolition and other

Waste generated by professionals who install or replace roofs

Waste generated by professionals who landscape or do otheryard care activities

Waste generated by professionals who construct or demolishbuildings

All other commercial self-haul waste that cannot be categorizedas either roofing, landscaping, or construction/demolition

In this study, the single-family residential subsector and the self-haul waste sector were sampled at disposal sites (transfer stations and landfills). Samples were obtained from randomly selected loads regularly arriving at these sites. For the 26 industry groups for commercial waste and for multifamily waste, samples were obtained from individual generators (businesses and apartment complexes) at their individual locations.

2.5 DIVIDING THE STATE INTO REGIONS

The state was divided into five regions to ensure adequate geographical and demographic representation throughout the state. The disposal sites were selected randomly within each


region to ensure that the waste samples were representative of the region as a whole and to allow for statistical analysis of the data. The stratified sampling plan targeted an equal number of disposal site samples for each region, ensuring that the information collected would be comparable statewide and that it would represent the breadth of communities within the state. Three steps were used to select the regions:

1. Identification of areas of the state with similar demographics and geographic features and tentative assignment of counties to regions.

2. Review of data on all of the counties in the state to confirm the original assignment.

3. Review of the designation of regions by the Advisory Group. Generator samples for each industry group and for the multifamily residential sectors were allocated to each region based approximately on the numbers of employees in each industry group in each region, or based on the number of apartment units in each region. (See Appendix A for details of the allocation of generator samples.)

Figure 1: Regions Used in the Study

M ou n t ain

Cen t ralValley

B ayA reaCoas t al

Sou t h ern


The five regions are shown in Figure 1 and are characterized as follows:

Coastal – includes the counties on the coast that are not in either the Bay Area or Southern regions. The Coastal region is more populated than the rural Mountain region and has a large agricultural component similar to the Central Valley.

Bay Area – includes the counties in the San Francisco Bay Area, which are the more metropolitan counties with a strong industrial component in the economy.

Southern – includes counties that are strongly industrial with large populations and important agricultural influences.

Mountain – includes counties that are primarily rural, with strong agricultural economies, low population density, and a low industrial base.

Central Valley – includes counties between the Sierra Nevada mountains and the Coast Range that have a major agricultural base with important population centers and some manufacturing.

In general, regions were designated so that selected counties were contiguous. The process for assigning counties to each region is described in more detail in Appendix A.

2.6 SELECTION OF SITES

Disposal sites for study were randomly selected from a comprehensive list of facilities in the state. Within each region, potential sites were eliminated from the list if they did not meet the minimum criteria required of sampling sites. The minimum criteria were that the site handles waste destined for final disposal (i.e. is not subject to any further processing or sorting), that it was possible to obtain credible tonnage data from all three waste sectors (i.e. commercial, residential and self-haul), and that it was possible to perform composition sampling for the residential and self-haul sectors. Of the sites meeting the minimum criteria, the first five randomly selected sites in each region were considered to be initial candidates for selection as sampling sites. The initial candidates were contacted and more detailed information on daily operations was obtained. In cases where a site was found to be unsuitable or unavailable, the next site on the random selection list was contacted until the required number of suitable sites were confirmed. After confirming the sampling sites, another randomization process was used to determine whether sampling at each site would occur during the winter or summer. Once sites were assigned to seasons, one site in each region in each season was selected as an area (waste shed) for generator sampling. In the Southern and Bay Area regions, an extra site was chosen where generator sampling would occur in both seasons, in order to expand the sampling areas in these larger regions.

2.7 CAPTURE AND SORTING OF WASTE SAMPLES

Waste from the single-family residential sector and the self-haul (residential and commercial) sector were gathered at five disposal sites (landfills or transfer stations) in each region, for a total of 25 sites. For businesses and multifamily residences, waste samples


were collected directly from these generators rather than at a disposal site. This allowed for more detailed analysis of these waste streams. CIWMB staff randomly selected two to three disposal sites per region for generator sampling. Waste samples were drawn from businesses and apartment/condominiums within a 20 mile radius of the selected sites. The geographic area from which generator samples were collected were called waste sheds. (See Table 71 in Appendix A for a list of waste sheds). Table 3 shows the number of samples that were collected for each sector.

Table 3: Numbers of Samples Collected from Each Sector

Sector Number of Samples Commercial 1,207 Residential 228 Single-Family Residential 148 Multifamily Residential 80

Self-Haul 247 Commercial Self-Haul 162 Residential Self-Haul 85

Total 1,682

See Appendix G for the detailed sampling scheme. Waste sampling occurred during two seasons to account for any seasonal variations in waste disposal patterns. The winter sampling occurred during February, March and April of 1999, and the summer sampling occurred during July, August, and September. Twelve sites were visited during the winter and thirteen during the summer for a total of 25 site visits. The waste was sorted and characterized into the categories included on California’s List of 57 Material Subtypes for Waste Sorting plus eight RPPC categories, as described in Appendix B. The material types include:

• • • • • • • • •

11 categories of paper; 6 categories of glass; 6 categories of metals; 6 categories of plastics; 8 categories of organic waste; 7 categories of construction/demolition waste; 5 categories of household hazardous waste; 7 categories of special waste; and 1 category of mixed residues that were too small to sort.

Plastic waste was further categorized into eight kinds of RPPCs. (See Figure 11 for a diagram of how plastics were sorted in the field.) These categories were proposed by CIWMB staff and approved by the Advisory Group.


2.7.1 COMMERCIAL GENERATOR SAMPLES The objectives of this task were 1) to estimate the composition of commercially collected waste that is disposed by commercial, industrial, and institutional generators in California and 2) to develop composition profiles for 26 types of generators, or business groups. (See Appendix E for a description of the groups.) Twelve-hundred samples were allocated among the 26 business groups. This ensured that the minimum number of samples required by the California Uniform Waste Disposal Characterization Method were collected from each business group. The samples were further allocated among the five regions of the state based on the relative contribution of each region to the statewide employment in each business group. Within each region, samples were allocated evenly between the two sampling seasons. For the Southern and Bay Area regions, two waste sheds were sampled during each season. Therefore, samples were further allocated among waste sheds based on the relative contribution of each waste shed to the regional employment in each business group. Within each business group in each waste shed, samples were distributed so that the majority of the samples were drawn from businesses who contribute large amounts of waste. This was accomplished using the 80/20 rule as a guide. This rule states that generally, 80% of the waste disposed by a group came from the largest businesses which make up about 20% of the group, and 20% of the waste came from the remaining 80% of the (smaller) businesses. This is explained more fully in Appendix A. Specific businesses were selected randomly using NameFinders, a research organization that uses Dun and Bradstreet business data. Over 10,000 business names were obtained to draw from, in order to ensure that a minimum of 1200 samples could be collected. The specific procedures used to identify, contact, and collect samples from businesses is described in Appendix A. Following the completion of each season of commercial generator sampling, subcontractor Veterans Assistance Network (VAN) contacted each of the sampled business sites to verify its SIC classification, and the number of employees working at the site.

2.7.2 RESIDENTIAL SAMPLES The objective of the residential waste sampling task was to estimate the composition of residential waste that is set out by single-family and multifamily residences for collection by professional waste haulers. Samples of single-family waste were gathered at the randomly selected disposal sites (see Appendix A). A total of 150 samples were targeted—30 in each of the five regions. This ensured that the minimum number of samples required by the California Uniform Waste Disposal Characterization Method were collected from each region. The 30 samples targeted in each region were evenly distributed among five different sites in the region. Thus, six samples were targeted at each of the 25 selected sites throughout the state. Samples of multifamily waste were gathered at randomly selected multifamily complexes in the state. This type of generator sampling was used because of the difficulty in obtaining pure loads of multifamily waste at disposal facilities – multifamily waste collected by haulers is often mixed with waste from businesses. The same areas used for commercial generator


sampling were used for multifamily generator sampling. Apartment complexes were selected randomly from available lists of complexes within each waste shed. A total of 80 multifamily samples was targeted, and samples were allocated among the regions based on the number of multifamily units in each region.

2.7.3 SELF-HAUL SAMPLES The objective of this task was to estimate the composition of waste disposed by residential and commercial self-haulers in California1. A total of 250 self-haul samples was targeted, or 50 samples per region. Due to the high variability in self-haul waste composition, more samples were collected from this sector than from single-family residences. Approximately two-thirds of the self-haul samples were allocated to commercial self-haul and one-third to residential self-haul because generally most of the tonnage in the self-haul stream is from commercial sources. The samples were collected at the five selected sites in each region for a total of 25 sites. Approximately 6 commercial and 4 residential samples were taken at each site for a total of ten samples per site.

2.8 VEHICLE SURVEYS

The objective of the vehicle surveys was to estimate the portion of California’s waste contributed by each of the residential, commercial, and self-haul sectors. The surveys provided an estimate of the fraction of the overall waste stream contributed by the residential, self-haul, and commercial sectors. To collect this data, vehicles were surveyed at the 25 randomly selected sampling sites (see Appendix A). All drivers entering the site during the survey period were interviewed.2 Drivers were asked to identify the sector source(s) of the waste in the load they were hauling, and the net weight of each load was recorded. A total of 3,648 surveys were completed.

3. RESULTS

3.1 COMPOSITION OF CALIFORNIA’S OVERALL WASTE STREAM

The objective of this portion of the study was to characterize the state’s entire disposed municipal solid waste stream, which combines all of the sectors and subsectors considered elsewhere in this study. Composition results for the overall waste stream are illustrated in Figure 2 and described in detail in Table 5. The material class Other Organic Waste accounts for approximately 35%

1 For purposes of this study, commercial self-haul loads were those hauled by a commercial enterprise (e.g. contractor, landscaper, etc.) even if the source of the waste was a residential dwelling. Residential self-haul loads were those loads transported by a resident from their home to the disposal site. 2 In rare cases, it was necessary to skip some vehicles to maintain safe and efficient traffic flows.


of disposed waste, and the Paper class accounts for about 30%. (See Table 5 for lists of materials belonging to each class, and see Appendix B for definitions of the materials.)

Figure 2: Overview of Overall Waste Stream

Paper30.2%

Glass2.8%

Metal6.1%

Plastic8.9%Special

3.1%

Other Organic35.1%

Household Hazardous

0.3%Mixed Residue

1.8%Construction & Demolition

11.6%

Food, a component of Other Organic Waste is the most prevalent material, representing 15.7% of the overall waste stream. Remainder/Composite Paper is also present in large amounts, representing 9.6% of the waste stream, and Leaves and Grass represents 7.9%. Together, materials from the Paper and Other Organic Waste classes comprise seven of the top ten materials in the overall waste stream. Table 4 presents the materials that account for approximately 65% of overall waste.



Table 4: Most Prevalent Materials in the Overall Waste Stream

Material Type Est. Pct. Est. Tons Cumulative Pct. Food 15.7% 5,584,506 15.7% Remainder/Composite Paper 9.6% 3,416,281 25.3% Leaves & Grass 7.9% 2,808,692 33.2% Remainder/Composite Organic 6.9% 2,453,912 40.1% Lumber 4.9% 1,746,001 45.1% Uncoated Corrugated Cardboard 4.6% 1,630,348 49.6% Other Miscellaneous Paper 4.4% 1,565,454 54.0% Newspaper 4.3% 1,521,186 58.3% Film Plastic 3.9% 1,377,438 62.2% Other Ferrous Metal 2.4% 866,716 64.6%




Paper 30.2% 10,742,707 Other Organic 35.1% 12,490,171Uncoated Corrugated Cardboard 4.6% 0.2% 1,630,348 Food 15.7% 0.6% 5,584,506Paper Bags 0.7% 0.0% 261,563 Leaves & Grass 7.9% 0.7% 2,808,692Newspaper 4.3% 0.3% 1,521,186 Prunings & Trimmings 2.2% 0.4% 790,727White Ledger Paper 2.3% 0.2% 812,752 Branches & Stumps 0.1% 0.1% 52,940Colored Ledger Paper 0.2% 0.0% 60,270 Agricultural Crop Residues 0.0% 0.0% 1,765Computer Paper 0.3% 0.1% 114,545 Manures 0.1% 0.1% 49,291Other Office Paper 1.7% 0.2% 591,080 Textiles 2.1% 0.3% 748,336Magazines and Catalogs 1.9% 0.1% 669,434 Remainder/Composite Organic 6.9% 0.5% 2,453,912Phone Books and Directories 0.3% 0.1% 99,793Other Miscellaneous Paper 4.4% 0.2% 1,565,454 Construction & Demolition 11.6% 4,110,526Remainder/Composite Paper 9.6% 0.4% 3,416,281 Concrete 1.2% 0.2% 418,600

Asphalt Paving 0.1% 0.1% 49,614Glass 2.8% 1,011,441 Asphalt Roofing 0.7% 0.2% 252,254

Clear Glass Bottles & Containers 1.4% 0.1% 506,214 Lumber 4.9% 0.5% 1,746,001Green Glass Bottles & Containers 0.4% 0.1% 154,191 Gypsum Board 1.1% 0.2% 402,784Brown Glass Bottles & Containers 0.5% 0.0% 167,529 Rock, Soil & Fines 1.3% 0.3% 461,437Other Colored Glass Bottles & Containers 0.0% 0.0% 6,859 Remainder/Composite C&D 2.2% 0.3% 779,836Flat Glass 0.1% 0.0% 23,206Remainer/Composite Glass 0.4% 0.1% 153,443 Household Hazardous Waste 0.3% 106,497


Tin/Steel Cans 1.0% 0.1% 339,570 Used Oil 0.0% 0.0% 1,579Major Appliances 0.1% 0.0% 23,257 Batteries 0.1% 0.0% 30,929Other Ferrous Metal 2.4% 0.3% 866,716 Remainder/Composite HHW 0.1% 0.0% 18,226Aluminum Cans 0.2% 0.0% 87,086Other Non-Ferrous Metal 0.3% 0.0% 93,548 Special Waste 3.1% 1,110,383Remainder/Composite Metal 2.1% 0.3% 753,903 Ash 0.1% 0.0% 21,464


HDPE Containers 0.8% 0.0% 275,944 Treated Medical Waste 0.0% 0.0% 6,478PETE Containers 0.5% 0.0% 160,615 Bulky Items 1.8% 0.6% 656,509Miscellaneous Plastic Containers 0.7% 0.1% 239,954 Tires 0.4% 0.2% 145,899Film Plastic 3.9% 0.2% 1,377,438 Remainder/Composite Special Waste 0.8% 0.3% 280,017Durable Plastic Items 1.8% 0.2% 631,536Remainder/Composite Plastic 1.3% 0.1% 476,224 Mixed Residue 1.8% 0.2% 637,938


Table 5: Composition of Overall Waste Stream

3.2 STATEWIDE TONNAGES BY SECTOR

3.2.1 VEHICLE SURVEY Vehicle surveys were used to estimate the percent contribution of each sector to the overall waste stream. Vehicle surveys were conducted at 24 of the 25 disposal facilities where disposal site waste samples were collected, and they were conducted on the same days as the collection of disposal site samples. (See Table 71 for a list of the sites that were visited.) Surveys were conducted for an approximately eight-hour period at each gatehouse leading into the particular facility. Surveyors recorded the net weight of each load and the sector and subsector to which it belonged. For loads that represented more than one sector/subsector (such as mixed commercial and multifamily waste), surveyors recorded the percentage of the load represented by each kind of waste, as estimated by the vehicle driver. A total of 2000 vehicle surveys were targeted for this study in order to provide adequate data. However, the actual number of surveys completed exceeded the target, as shown in Table 6. To determine the tons of waste disposed from each sector, the percentages that were obtained from vehicle surveys were applied to the 1998 tons of waste disposed in each region, as recorded in the CIWMB’s Disposal Reporting System. Tonnage allocations across sectors and subsectors were determined by

1. keeping track of the tons of waste belonging to each sector and subsector that entered each facility on the appropriate survey day,

2. applying the proportions found at the facility level to the known 1998 tons of waste disposed in each region, with weighting according to the amount of waste that entered each facility in 1998,

3. applying the proportions found at the regional level to the known 1998 statewide tons of waste (35,535,453 tons), with weighting according to the amount of waste disposed in each region in 1998.

See Section A.10 of Appendix A for an explanation of the calculations. Both the percentages and tonnage ascribed to each sector/subsector are presented in Table 7.

Table 6: Numbers of Vehicles Surveyed by Region and Season

Coastal Bay Area Southern 3 Mountain Central Totals Winter 262 324 813 371 198 1,968 Summer 281 845 84 116 354 1,680 Totals 543 1,169 897 487 552 3,648

3 There were two reasons for the relatively small number of vehicle surveys conducted in the Southern region during the summer. First, both of the sites that were selected for summer sampling and surveying had fairly light vehicle traffic compared to other sites considered in this study. Second, it was determined that the surveys taken at one of the Southern region sites, Universal Refuse Removal and Recycling, were not representative of the entire spectrum of waste entering that site. The 16 vehicles surveyed at the Universal Refuse site are not included in Table 6 and were not included in the analysis of vehicle surveys.


3.2.2 STATEWIDE PERCENTAGES AND TONNAGES BY SECTOR Table 7 shows the estimated contributions of each sector of the waste stream.

Table 7: Statewide Tonnage and Percentage of Waste Stream by Sector 4


+ / -

Est. Tons Statewide

Commercial 48.8% 2.8% 17,358,359

Residential 38.1% 3.0% 13,525,504 Single-family residential 28.0% 2.7% 9,955,739 Multifamily residential 10.0% 1.6% 3,569,888

Self-haul 13.1% 1.5% 4,651,591 Commercial self-haul 10.5% 1.4% 3,739,696 Residential self-haul 2.6% 0.4% 911,770

Totals 100.0% 35,535,453 Confidence intervals calculated at the 90% confidence level. Numbers may not total 100% due to rounding. Tonnages are based on 1998 tons reported, by region, through California’s Disposal Reporting System.

Commercial waste and residential waste include all waste collected and transported to disposal sites by professional waste haulers. Self-haul waste includes both commercial and residential wastes that are hauled by an individual or business other than a professional waste hauler whose primary business is not hauling waste (e.g. an individual, a construction company, a landscaper, etc). For purposes of this study, commercial self-haul loads were those hauled by a commercial enterprise (e.g. contractor, landscaper, etc.) even if the source of the waste was a residential dwelling. Residential self-haul loads were those loads transported by a resident from their home to the disposal site. Residential waste from all sources accounts for 40.7% of the state’s waste stream, while 59.3% comes from non-residential sources. Overall, the per-capita disposal rate for the state was approximately 1.07 tons per person per year in 1999. The per-capita disposal rate for residential waste (single-family and multifamily) was approximately 0.41 tons per person per year. Table 8 shows the residential per-capita disposal rates for each region.

Table 8: Annual Residential Disposed Waste Per-Capita for Each Region

Region

Population

Residential Disposed Tons

Per-Capita Residential Disposal Rate

(Tons per Resident per Year) Coastal 1,363,600 604,752 0.44 Bay Area 6,256,500 2,655,988 0.42 Southern 20,340,700 8,437,874 0.41 Mountain 698,910 172,179 0.25 Central 4,590,800 1,646,735 0.36

Statewide 33,250,510 13,517,528 0.41 Numbers may not total exactly due to rounding.

4 These figures were calculated based on vehicle surveys conducted in 1999 and applied to statewide tonnage as reported in 1998 through the CIWMB’s Disposal Reporting System.



3.2.3 COMMERCIAL SELF-HAUL ACTIVITIES Drivers of commercial self-haul vehicles were also asked to describe the origin of their waste as either roofing, landscaping, construction/demolition, or other commercial activities. Table 9 shows the results.

Table 9: Contribution of Specific Activities to the Commercial Self-Haul Subsector


+ / -

Est. Tons Statewide

Construction & Demolition 4.5% 1.0% 1,584,303 Roofing 1.1% 0.8% 391,881 Landscaping 0.9% 0.3% 320,649 Other Commercial 4.1% 1.0% 1,442,862

Totals 10.5% 1.4% 3,739,696 Confidence intervals calculated at the 90% confidence level. Numbers may not total exactly due to rounding.

3.3 COMMERCIAL WASTE

The objective of this portion of the study was to characterize California’s commercial waste stream at the state level. Commercial waste is defined as waste disposed by businesses, industries, and public organizations that is collected and transported by professional waste haulers. This section presents composition findings for the statewide commercial sector as a whole, as well as findings for individual industry groups. As shown in Table 7 (page 13), the commercial sector accounts for approximately 48.8% of California’s municipal solid waste stream.

3.3.1 THE OVERALL COMMERCIAL SECTOR DESCRIPTION OF SAMPLES Samples of commercial waste were obtained at generator sites (the sites of individual businesses, organizations, and institutions) after arrangements were made with the managers of each site. Appendix A describes the site arrangements and sampling logistics for this process. In total, 1,207 waste samples were collected from generators belonging to the 26 industry groups discussed in this report. Table 10 provides a breakdown of the commercial generator samples by region and industry group, and Table 11 provides a profile of the numbers of employees at the commercial sites that were sampled. There were 532 samples in the winter and 675 samples in the summer. Samples were distributed among regions based on employment in each industry group in each region. (See Appendix A for a full description of the allocation, capture, and analysis of waste samples. See Appendix F for employment data for each industry group in each region and statewide.)

Table 10: Numbers of Commercial Samples Collected by Industry Group and Region

Coastal Bay Area Southern Mountain Central Totals A - Finance / Insurance / Real Estate / Legal 2 11 27 2 6 48 B - Retail Trade - Restaurants 2 11 30 2 6 51 C - Retail Trade - Other 2 14 28 2 5 51 D - Services - Other Misc. 2 11 29 2 6 50 E - Wholesale Trade - Nondurable Goods 5 8 28 4 8 53 F - Retail Trade - Automotive Dealers & Service Stations 2 9 31 4 7 53 G - Services - Other Professional 3 11 27 2 6 49 H - Retail Trade - Food Store 3 9 30 2 8 52 I - Construction 3 9 24 2 7 45 J - Services - Medical / Health 2 10 27 2 9 50 K - Manufacturing - Printing / Publishing 3 10 26 3 4 46 L - Services - Business Services 1 12 24 2 4 43 M - Services - Education 2 7 24 2 7 42 N - Public Administration 4 8 23 2 6 43 O - Services - Hotels / Lodging 2 9 23 3 4 41 P - Trucking & Warehousing 1 7 22 3 9 42 Q - Wholesale Trade - Durable Goods 2 9 25 2 4 42 R - Manufacturing - Other 2 5 31 2 5 45 S - Transportation - Other 3 11 21 2 4 41 T - Manufacturing - Electronic Equipment 3 19 19 3 44 U - Manufacturing - Food / Kindred 3 7 14 2 15 41 V - Manufacturing - Lumber & Wood Products 6 5 15 3 11 40 W - Manufacturing - Transportation Equipment 3 7 32 1 3 46 X - Retail Trade - Building Material & Garden 2 9 21 2 7 41 Y - Manufacturing - Industrial / Machinery 3 20 20 5 48 Z - AM Lumped Group 7 21 12 5 15 60 Totals 73 269 633 58 174 1,207



Table 11: Distribution of the Number of Employees at Commercial Sites that were Sampled

1-4 5-9 10-19 20-49 50-99 100-499 500-999 1000+ Totals A - Finance / Insurance / Real Estate / Legal 8 12 10 7 3 5 1 2 48 B - Retail Trade - Restaurants 6 7 19 17 2 51 C - Retail Trade - Other 20 12 10 9 51 D - Services - Other Misc. 11 19 8 9 2 1 50 E - Wholesale Trade - Nondurable Goods 9 9 16 15 1 3 53 F - Retail Trade - Automotive Dealers & Service Stations 12 20 9 7 4 1 53 G - Services - Other Professional 19 10 10 5 3 2 49 H - Retail Trade - Food Store 14 8 7 13 6 4 52 I - Construction 13 16 4 11 1 45 J - Services - Medical / Health 12 10 7 11 4 5 1 50 K - Manufacturing - Printing / Publishing 7 8 13 12 3 3 46 L - Services - Business Services 8 5 7 14 3 6 43 M - Services - Education 2 2 3 10 10 12 1 2 42 N - Public Administration 1 3 10 5 19 1 4 43 O - Services - Hotels / Lodging 2 2 8 7 2 20 41 P - Trucking & Warehousing 9 8 6 11 4 4 42 Q - Wholesale Trade - Durable Goods 8 16 8 8 2 42 R - Manufacturing - Other 6 1 11 12 7 7 1 45 S - Transportation - Other 5 9 11 6 4 6 41 T - Manufacturing - Electronic Equipment 2 2 2 4 9 22 3 44 U - Manufacturing - Food / Kindred 1 7 6 6 19 1 1 41 V - Manufacturing - Lumber & Wood Products 9 5 13 9 2 2 40 W - Manufacturing - Transportation Equipment 1 5 2 5 9 16 2 6 46 X - Retail Trade - Building Material & Garden 9 14 9 8 1 41 Y - Manufacturing - Industrial / Machinery 6 4 11 7 6 6 5 3 48 Z - AM Lumped Group 7 3 8 11 14 14 3 60 Totals 206 211 219 244 109 181 15 22 1,207

VOLUME AND DENSITY FINDINGS Table 12 shows the estimated average disposal volume and average waste density for each industry group considered in the study. These figures were calculated based on information collected about the waste density (sample weight per volume), dumpster volume, dumpster fullness, frequency of waste pick-up, and number of employees at each participating generator site. (See Appendix A for a description of how the base information was collected and used.)

Table 12: Annual Disposal Volume and Waste Density by Industry Group

Industry Group

Avg. Disp. Vol. (annual cu. yds per employee)

+ / -

Avg. Waste Density (pounds per cu. yd.)

+ / -

A - Finance / Insurance / Real Estate / Legal 5.1 8.5 87.6 11.1 B - Retail Trade - Restaurants 47.4 48.8 109.0 28.1 C - Retail Trade - Other 44.0 36.5 72.1 14.8 D - Services - Other Misc. 16.1 12.7 89.5 13.0 E - Wholesale Trade - Nondurable Goods 18.1 8.0 86.8 25.1 F - Retail Trade - Auto Dealers & Svc. Stations 12.6 6.0 83.5 19.2 G - Services - Other Professional 19.8 14.8 104.4 22.5 H - Retail Trade - Food Store 56.9 31.9 84.4 16.8 I - Construction 43.7 41.4 116.2 26.0 J - Services - Medical / Health 34.0 13.9 74.7 8.1 K - Manufacturing - Printing / Publishing 15.1 5.4 87.5 19.8 L - Services - Business Services 32.1 31.4 87.1 20.9 M - Services - Education 19.3 8.0 72.5 11.2 N - Public Administration 8.0 3.8 88.9 21.6 O - Services - Hotels / Lodging 35.7 11.5 97.1 14.0 P - Trucking & Warehousing 33.2 25.8 94.6 37.3 Q - Wholesale Trade - Durable Goods 23.9 18.5 64.5 23.1 R - Manufacturing - Other 42.9 75.6 121.7 23.8 S - Transportation - Other 28.7 27.0 73.4 23.8 T - Manufacturing - Electronic Equipment 13.8 9.6 62.5 8.7 U - Manufacturing - Food / Kindred 35.8 23.7 73.5 15.3 V - Manufacturing - Lumber & Wood Products 39.1 16.4 134.2 36.8 W - Manufacturing - Transportation Equipment 8.5 9.2 75.9 33.7 X - Retail Trade - Building Material & Garden 46.1 30.5 121.2 31.5 Y - Manufacturing - Industrial / Machinery 5.1 2.9 69.0 14.2 Z - AM Lumped Group 17.8 13.5 67.2 21.8

Overall Means 25.2 3.7 84.4 4.4 Confidence intervals calculated at the 90% confidence level.

AVERAGE DISPOSAL RATES Table 13 shows the estimated average per-employee disposal rate and estimated statewide disposal for each industry group considered in the study. These figures were calculated based on information collected about the waste density (sample weight per volume), dumpster volume, dumpster fullness, frequency of waste pick-up, and number of employees at each participating generator site. Table 14 shows the relative contribution of each industry group to the state’s entire Commercial sector waste. (See Appendix A for a description of how the base information was collected and used.)


Table 13: Per-Employee Disposal Rate and Estimated Contribution of Each Industry Group to

Commercial Waste

Industry Group

Avg. Disp. Rate (tons per employee

per year)

Statewide

Employment

Est. Statewide Disposal

(tons per year)

A - Finance / Insurance / Real Estate / Legal 0.3 1,208,364 322,502 B - Retail Trade - Restaurants 3.1 853,496 2,622,515 C - Retail Trade - Other 1.9 836,028 1,577,262 D - Services - Other Misc. 0.9 1,070,033 919,135 E - Wholesale Trade - Nondurable Goods 0.9 410,917 382,924 F - Retail Trade - Auto Dealers & Svc. Stations 0.6 280,545 175,403 G - Services - Other Professional 1.2 663,374 814,533 H - Retail Trade - Food Store 2.9 351,497 1,003,044 I - Construction 3.0 458,468 1,386,113 J - Services - Medical / Health 1.5 1,349,874 2,040,526 K - Manufacturing - Printing / Publishing 0.8 211,145 165,594 L - Services - Business Services 1.7 611,082 1,015,819 M - Services - Education 0.8 919,623 763,817 N - Public Administration 0.4 659,925 278,112 O - Services - Hotels / Lodging 2.1 223,203 459,789 P - Trucking & Warehousing 1.9 131,347 245,569 Q - Wholesale Trade - Durable Goods 0.9 617,125 566,863 R - Manufacturing - Other 3.1 167,736 520,486 S - Transportation - Other 1.3 161,146 202,160 T - Manufacturing - Electronic Equipment 0.5 266,397 136,275 U - Manufacturing - Food / Kindred 1.6 152,800 238,668 V - Manufacturing - Lumber & Wood Products 3.1 34,339 107,251 W - Manufacturing - Transportation Equipment 0.4 137,964 52,606 X - Retail Trade - Building Material & Garden 3.3 134,247 446,541 Y - Manufacturing - Industrial / Machinery 0.2 221,676 46,172 Z - AM Lumped Group 0.7 1,221,000 868,681

Overall Mean and Totals 1.3 13,353,351 17,358,359 Employment figures were based on 1998 employment data, the most recent data available. Disposal tons in this table may not match exactly the tons reported in industry group composition tables because of rounding.


Table 14: Relative Contribution of Each Industry Group to Commercial Waste

Industry Group

Est. Statewide Disposal

(tons per year)

Est. Percentage of Commercial Sector

Waste

B - Retail Trade - Restaurants 2,622,515 15.1% J - Services - Medical / Health 2,040,526 11.8% C - Retail Trade - Other 1,577,262 9.1% I - Construction 1,386,113 8.0% L - Services - Business Services 1,015,819 5.9% H - Retail Trade - Food Store 1,003,044 5.8% D - Services - Other Misc. 919,135 5.3% Z - AM Lumped Group 868,681 5.0% G - Services - Other Professional 814,533 4.7% M - Services - Education 763,817 4.4% Q - Wholesale Trade - Durable Goods 566,863 3.3% R - Manufacturing - Other 520,486 3.0% O - Services - Hotels / Lodging 459,789 2.6% X - Retail Trade - Building Material & Garden 446,541 2.6% E - Wholesale Trade - Nondurable Goods 382,924 2.2% A - Finance / Insurance / Real Estate / Legal 322,502 1.9% N - Public Administration 278,112 1.6% P - Trucking & Warehousing 245,569 1.4% U - Manufacturing - Food / Kindred 238,668 1.4% S - Transportation - Other 202,160 1.2% F - Retail Trade - Auto Dealers & Svc. Stations 175,403 1.0% K - Manufacturing - Printing / Publishing 165,594 1.0% T - Manufacturing - Electronic Equipment 136,275 0.8% V - Manufacturing - Lumber & Wood Products 107,251 0.6% W - Manufacturing - Transportation Equipment 52,606 0.3% Y - Manufacturing - Industrial / Machinery 46,172 0.3%

Total 17,358,359 100.0% Disposal tons in this table may not match exactly the tons reported in industry group composition tables because of rounding.

OVERALL COMMERCIAL WASTE COMPOSITION Composition results for commercial waste are illustrated in Figure 3 and described in detail in Table 16. The overall commercial composition was developed by aggregating data from each of the 26 industry groups (see Section A.10). The material class Paper accounts for approximately 39% of disposed commercial waste, and the class Other Organic accounts for about 31%. (See Table 16 for lists of materials belonging to each class, and see Appendix B for definitions of the materials.)



Figure 3: Overview of Commercial Waste

Metal6.0%

31.3%Other Organic

Glass2.4%

Paper39.0%

Household Hazardous

0.3%Mixed Residue

0.5%

Construction & Demolition

6.4%

Special4.1%

Plastic9.8%

Food, a component of Other Organic Waste is the most prevalent material, representing 16.3% of commercial waste. Remainder/Composite Paper is also present in large amounts, representing 13.2% of the sector’s waste. Together, materials from the Paper and Other Organic Waste classes comprise eight of the top ten materials in commercial waste. Table 15 presents the materials that account for approximately 68% of commercial waste.

Material Type Est. Pct. Est. Tons Cumulative Pct. Food 16.3% 2,829,194 16.3% Remainder/Composite Paper 13.2% 2,282,775 29.4% Leaves & Grass 6.9% 1,205,147 36.4% Uncoated Corrugated Cardboard 6.6% 1,137,254 42.9% Other Miscellaneous Paper 5.0% 860,479 47.9% Remainder/Composite Organic 4.6% 792,085 52.5% Film Plastic 4.5% 772,721 56.9% White Ledger Paper 4.2% 729,144 61.1% Lumber 3.8% 658,061 64.9% Newspaper 3.6% 629,836 68.5%


Table 15: Most Prevalent Materials in Commercial Waste



Paper 39.0% 6,776,011 Other Organic 31.3% 5,437,472Uncoated Corrugated Cardboard 6.6% 0.5% 1,137,254 Food 16.3% 1.0% 2,829,194Paper Bags 0.7% 0.1% 121,339 Leaves & Grass 6.9% 1.0% 1,205,147Newspaper 3.6% 0.3% 629,836 Prunings & Trimmings 1.1% 0.4% 197,398White Ledger Paper 4.2% 0.5% 729,144 Branches & Stumps 0.0% 0.0% 2,103Colored Ledger Paper 0.3% 0.0% 51,279 Agricultural Crop Residues 0.0% 0.0% 1,506Computer Paper 0.6% 0.1% 109,639 Manures 0.3% 0.3% 49,291Other Office Paper 2.4% 0.3% 420,616 Textiles 2.1% 0.5% 360,747Magazines and Catalogs 2.3% 0.3% 393,755 Remainder/Composite Organic 4.6% 0.6% 792,085Phone Books and Directories 0.2% 0.1% 39,896Other Miscellaneous Paper 5.0% 0.3% 860,479 Construction & Demolition 6.4% 1,118,116Remainder/Composite Paper 13.2% 0.8% 2,282,774 Concrete 0.4% 0.2% 77,650

Asphalt Paving 0.1% 0.1% 14,819Glass 2.4% 417,841 Asphalt Roofing 0.0% 0.0% 675

Clear Glass Bottles & Containers 1.3% 0.1% 224,863 Lumber 3.8% 0.7% 658,061Green Glass Bottles & Containers 0.3% 0.0% 43,951 Gypsum Board 0.4% 0.1% 69,970Brown Glass Bottles & Containers 0.3% 0.1% 52,098 Rock, Soil & Fines 0.8% 0.2% 133,556Other Colored Glass Bottles & Containers 0.0% 0.0% 4,483 Remainder/Composite C&D 0.9% 0.2% 163,386Flat Glass 0.0% 0.0% 8,480Remainer/Composite Glass 0.5% 0.1% 83,965 Household Hazardous Waste 0.3% 56,828


Tin/Steel Cans 0.9% 0.1% 147,891 Used Oil 0.0% 0.0% 660Major Appliances 0.0% 0.0% 8,180 Batteries 0.1% 0.1% 20,238Other Ferrous Metal 2.3% 0.4% 401,099 Remainder/Composite HHW 0.1% 0.0% 13,826Aluminum Cans 0.2% 0.0% 35,236Other Non-Ferrous Metal 0.2% 0.0% 41,923 Special Waste 4.1% 716,524Remainder/Composite Metal 2.4% 0.4% 408,868 Ash 0.1% 0.0% 12,122


HDPE Containers 0.7% 0.1% 114,828 Treated Medical Waste 0.0% 0.0% 2,756PETE Containers 0.4% 0.0% 74,793 Bulky Items 2.4% 1.1% 418,530Miscellaneous Plastic Containers 0.7% 0.1% 127,347 Tires 0.4% 0.2% 72,255Film Plastic 4.5% 0.4% 772,721 Remainder/Composite Special Waste 1.2% 0.5% 210,844Durable Plastic Items 1.9% 0.3% 325,297Remainder/Composite Plastic 1.7% 0.1% 292,047 Mixed Residue 0.5% 0.1% 85,338


Table 16: Composition of Commercial Waste

3.3.2 COMPOSITION BY INDUSTRY GROUP The study called for 1,200 commercial generator samples, which were allocated to 26 industry groups organized according to Standard Industrial Classification (SIC) codes (see Appendix E for definitions of these groups). The following industry groups were included:

•

• • • •

•

• • • • •

• • •

• • •

• • •

• •

•

•

•

•

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• •

•

•

•

•

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A - Finance / Insurance / Real Estate / Legal B - Retail Trade - Restaurants C - Retail Trade - Other D - Services - Other Misc. E - Wholesale Trade - Nondurable Goods F - Retail Trade - Automotive Dealers & Service Stations G - Services - Other Professional H - Retail Trade - Food Store I - Construction J - Services - Medical / Health K - Manufacturing - Printing / Publishing L - Services - Business Services M - Services – Education N - Public Administration

O - Services - Hotels / Lodging P - Trucking & Warehousing Q - Wholesale Trade - Durable Goods R - Manufacturing - Other S - Transportation - Other T - Manufacturing - Electronic Equipment U - Manufacturing - Food / Kindred V - Manufacturing - Lumber & Wood Products W - Manufacturing - Transportation Equipment X - Retail Trade - Building Material & Garden Y - Manufacturing - Industrial / Machinery Z - AM Lumped Group

The last grouping, “Z - AM Lumped Group” includes several industry groups, each of which contributes relatively little to the state’s commercial waste stream. The lumped group includes the following industries:

Z - Agriculture / Fisheries AA - Manufacturing - Instruments / Related AB - Communications AC - Manufacturing - Primary / Fabricated Metal AD - Manufacturing - Apparel / Textile AE - Manufacturing - Furniture / Fixtures AF - Services - Motion Pictures

AG - Manufacturing - Chemical / Allied AH - Retail Trade - General Merchandise Store AI - Mining AJ - Transportation - Air AK - Utilities AL - Manufacturing - Paper / Allied AM - Forestry

Samples were allocated to each industry group and then were allocated to each of the state’s five regions based on the relative contribution of each region to the employment in each industry group. (See Table 73 of Appendix A for a breakdown of the original sample



allocation by region and industry group, and see Table 10 of this section for a count of the samples actually obtained by region and industry group. Appendix A also contains a detailed description of sample allocation procedures.) Samples were further allocated to the selected waste sheds within each region based on the relative contribution of each waste shed to the employment in each industry group. Table 17 through Table 42 present the detailed composition results for each of 26 industry groups.

Table 17: Composition of Waste from Group A: Finance / Insurance / Real Estate / Legal


Paper 50.4% 162,494 Other Organic 25.6% 82,560Uncoated Corrugated Cardboard 7.8% 2.2% 25,074 Food 15.0% 3.9% 48,285Paper Bags 0.5% 0.1% 1,751 Leaves & Grass 6.1% 3.6% 19,725Newspaper 4.4% 1.0% 14,109 Prunings & Trimmings 0.4% 0.3% 1,293White Ledger Paper 11.2% 2.9% 36,039 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.4% 0.1% 1,308 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.9% 0.7% 2,842 Manures 0.0% 0.0% 0Other Office Paper 4.1% 1.5% 13,357 Textiles 1.0% 0.5% 3,077Magazines and Catalogs 3.7% 1.4% 11,887 Remainder/Composite Organic 3.2% 1.5% 10,181Phone Books and Directories 0.3% 0.1% 841Other Miscellaneous Paper 6.0% 1.2% 19,324 Construction & Demolition 4.3% 13,796Remainder/Composite Paper 11.2% 1.4% 35,961 Concrete 0.0% 0.0% 32

Asphalt Paving 0.0% 0.0% 0Glass 2.7% 8,569 Asphalt Roofing 0.0% 0.0% 0

Clear Glass Bottles & Containers 1.7% 0.5% 5,418 Lumber 3.0% 2.8% 9,763Green Glass Bottles & Containers 0.2% 0.1% 800 Gypsum Board 0.0% 0.0% 0Brown Glass Bottles & Containers 0.3% 0.1% 853 Rock, Soil & Fines 0.0% 0.0% 52Other Colored Glass Bottles & Containers 0.1% 0.0% 216 Remainder/Composite C&D 1.2% 0.8% 3,949Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.4% 0.3% 1,281 Household Hazardous Waste 1.0% 3,231

Paint 0.0% 0.0% 7Metal 3.8% 12,143 Vehicle & Equipment Fluids 0.5% 0.5% 1,645

Tin/Steel Cans 0.4% 0.1% 1,180 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.5% 0.4% 1,579Other Ferrous Metal 2.3% 1.2% 7,574 Remainder/Composite HHW 0.0% 0.0% 0Aluminum Cans 0.3% 0.1% 1,024Other Non-Ferrous Metal 0.2% 0.1% 535 Special Waste 5.0% 16,047Remainder/Composite Metal 0.6% 0.2% 1,831 Ash 0.3% 0.2% 1,072

Sewage Solids 0.0% 0.0% 0Plastic 6.7% 21,694 Industrial Sludge 0.0% 0.0% 0

HDPE Containers 0.4% 0.1% 1,140 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.4% 0.1% 1,271 Bulky Items 4.6% 3.5% 14,893Miscellaneous Plastic Containers 0.7% 0.1% 2,309 Tires 0.0% 0.0% 0Film Plastic 3.2% 0.5% 10,273 Remainder/Composite Special Waste 0.0% 0.0% 81Durable Plastic Items 0.5% 0.1% 1,675Remainder/Composite Plastic 1.6% 0.4% 5,025 Mixed Residue 0.6% 0.4% 1,968

Sample count: 48 Totals 100.0% 322,501Confidence intervals calculated at the 90% confidence level. Percentages for materials may not total 100% due to rounding.


Table 18: Composition of Waste from Group B: Retail Trade - Restaurants


Paper 25.0% 655,769 Other Organic 56.8% 1,490,550Uncoated Corrugated Cardboard 5.9% 1.0% 154,654 Food 56.0% 3.2% 1,467,819Paper Bags 0.5% 0.1% 13,234 Leaves & Grass 0.2% 0.1% 4,743Newspaper 2.5% 0.7% 66,732 Prunings & Trimmings 0.0% 0.0% 300White Ledger Paper 0.2% 0.1% 5,264 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.1% 0.1% 2,566 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.2% 0.2% 4,553 Manures 0.0% 0.0% 0Other Office Paper 0.3% 0.1% 7,342 Textiles 0.3% 0.1% 7,957Magazines and Catalogs 0.2% 0.1% 4,520 Remainder/Composite Organic 0.4% 0.1% 9,731Phone Books and Directories 0.0% 0.0% 80Other Miscellaneous Paper 2.2% 0.4% 57,893 Construction & Demolition 4.4% 115,783Remainder/Composite Paper 12.9% 2.1% 338,933 Concrete 0.0% 0.0% 0


Clear Glass Bottles & Containers 1.7% 0.3% 43,759 Lumber 0.7% 0.5% 19,330Green Glass Bottles & Containers 0.7% 0.2% 18,565 Gypsum Board 0.2% 0.2% 5,478Brown Glass Bottles & Containers 0.6% 0.1% 14,994 Rock, Soil & Fines 0.0% 0.0% 0Other Colored Glass Bottles & Containers 0.1% 0.0% 1,314 Remainder/Composite C&D 2.7% 1.2% 70,141Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.2% 0.1% 4,115 Household Hazardous Waste 0.0% 88

Paint 0.0% 0.0% 0Metal 3.4% 88,675 Vehicle & Equipment Fluids 0.0% 0.0% 0

Tin/Steel Cans 1.9% 0.5% 49,215 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.0% 0.0% 82Other Ferrous Metal 0.1% 0.1% 3,282 Remainder/Composite HHW 0.0% 0.0% 6Aluminum Cans 0.1% 0.0% 2,594Other Non-Ferrous Metal 0.4% 0.2% 9,490 Special Waste 0.0% 177Remainder/Composite Metal 0.9% 0.8% 24,095 Ash 0.0% 0.0% 177


HDPE Containers 0.8% 0.1% 20,911 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.2% 0.0% 4,649 Bulky Items 0.0% 0.0% 0Miscellaneous Plastic Containers 0.4% 0.1% 9,187 Tires 0.0% 0.0% 0Film Plastic 4.4% 0.5% 116,537 Remainder/Composite Special Waste 0.0% 0.0% 0Durable Plastic Items 0.7% 0.3% 17,254Remainder/Composite Plastic 0.6% 0.1% 15,385 Mixed Residue 0.2% 0.1% 4,804

Sample count: 51 Totals 100.0% 2,622,518Confidence intervals calculated at the 90% confidence level. Percentages for materials may not total 100% due to rounding.


Table 19: Composition of Waste from Group C: Retail Trade - Other


Paper 39.8% 628,523 Other Organic 30.6% 483,265Uncoated Corrugated Cardboard 12.0% 2.6% 190,057 Food 8.0% 1.8% 125,943Paper Bags 0.7% 0.1% 11,169 Leaves & Grass 2.9% 1.5% 46,047Newspaper 4.0% 1.1% 63,357 Prunings & Trimmings 0.9% 0.5% 13,623White Ledger Paper 2.0% 0.9% 32,081 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.1% 0.0% 1,708 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 1.7% 0.9% 26,809 Manures 4.9% 4.5% 77,762Other Office Paper 1.3% 0.3% 20,705 Textiles 6.0% 4.7% 94,150Magazines and Catalogs 1.4% 0.4% 21,994 Remainder/Composite Organic 8.0% 4.0% 125,741Phone Books and Directories 0.1% 0.1% 1,803Other Miscellaneous Paper 7.5% 2.0% 118,614 Construction & Demolition 6.4% 101,510Remainder/Composite Paper 8.9% 1.5% 140,225 Concrete 0.1% 0.1% 2,059


Clear Glass Bottles & Containers 1.6% 0.5% 25,307 Lumber 4.9% 1.6% 77,745Green Glass Bottles & Containers 0.3% 0.1% 4,748 Gypsum Board 0.1% 0.1% 1,505Brown Glass Bottles & Containers 0.3% 0.2% 4,869 Rock, Soil & Fines 1.2% 1.2% 18,903Other Colored Glass Bottles & Containers 0.0% 0.0% 261 Remainder/Composite C&D 0.1% 0.1% 1,284Flat Glass 0.1% 0.1% 1,360Remainer/Composite Glass 0.1% 0.0% 1,303 Household Hazardous Waste 0.3% 4,597

Paint 0.1% 0.1% 1,647Metal 7.7% 121,511 Vehicle & Equipment Fluids 0.0% 0.0% 0

Tin/Steel Cans 0.3% 0.1% 5,342 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.2% 0.1% 2,950Other Ferrous Metal 4.9% 3.7% 76,853 Remainder/Composite HHW 0.0% 0.0% 0Aluminum Cans 0.2% 0.1% 3,548Other Non-Ferrous Metal 0.1% 0.0% 1,807 Special Waste 2.0% 30,881Remainder/Composite Metal 2.2% 0.9% 33,961 Ash 0.0% 0.0% 0


HDPE Containers 0.6% 0.2% 9,333 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.6% 0.1% 9,014 Bulky Items 1.8% 1.7% 27,646Miscellaneous Plastic Containers 0.4% 0.1% 6,886 Tires 0.0% 0.0% 0Film Plastic 4.7% 1.4% 74,703 Remainder/Composite Special Waste 0.2% 0.2% 3,235Durable Plastic Items 1.4% 0.3% 21,560Remainder/Composite Plastic 2.3% 0.6% 36,229 Mixed Residue 0.7% 0.3% 11,405



Table 20: Composition of Waste from Group D: Services - Other Misc.


Paper 33.2% 304,891 Other Organic 30.3% 278,498Uncoated Corrugated Cardboard 6.8% 0.9% 62,512 Food 12.6% 3.4% 115,963Paper Bags 0.7% 0.1% 6,630 Leaves & Grass 6.0% 2.5% 54,780Newspaper 6.1% 1.9% 56,021 Prunings & Trimmings 1.1% 0.8% 10,543White Ledger Paper 1.2% 0.4% 11,417 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.1% 0.0% 1,178 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.3% 0.2% 2,443 Manures 0.0% 0.0% 0Other Office Paper 1.0% 0.2% 9,358 Textiles 4.7% 2.7% 43,247Magazines and Catalogs 1.6% 0.6% 15,039 Remainder/Composite Organic 5.9% 1.1% 53,965Phone Books and Directories 0.3% 0.2% 2,557Other Miscellaneous Paper 3.5% 0.5% 31,954 Construction & Demolition 4.8% 44,261Remainder/Composite Paper 11.5% 2.0% 105,781 Concrete 0.0% 0.0% 0


Clear Glass Bottles & Containers 1.2% 0.4% 11,417 Lumber 3.2% 1.5% 29,019Green Glass Bottles & Containers 0.4% 0.2% 3,425 Gypsum Board 0.0% 0.0% 0Brown Glass Bottles & Containers 0.2% 0.1% 1,547 Rock, Soil & Fines 1.3% 1.2% 11,725Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 0.4% 0.2% 3,518Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.7% 0.4% 6,344 Household Hazardous Waste 0.5% 4,479


Tin/Steel Cans 1.9% 0.5% 17,410 Used Oil 0.0% 0.0% 36Major Appliances 0.0% 0.0% 0 Batteries 0.0% 0.0% 378Other Ferrous Metal 5.2% 2.1% 47,826 Remainder/Composite HHW 0.4% 0.4% 3,610Aluminum Cans 0.2% 0.0% 1,919Other Non-Ferrous Metal 0.4% 0.1% 3,611 Special Waste 3.7% 33,762Remainder/Composite Metal 6.8% 2.9% 62,084 Ash 0.0% 0.0% 195


HDPE Containers 1.5% 0.4% 13,398 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.6% 0.1% 5,274 Bulky Items 1.2% 1.1% 11,246Miscellaneous Plastic Containers 0.5% 0.1% 4,576 Tires 2.4% 1.9% 21,764Film Plastic 4.6% 0.8% 42,726 Remainder/Composite Special Waste 0.1% 0.0% 558Durable Plastic Items 1.8% 0.5% 16,218Remainder/Composite Plastic 1.2% 0.2% 10,836 Mixed Residue 0.5% 0.2% 4,640



Table 21: Composition of Waste from Group E: Wholesale Trade - Nondurable Goods


Paper 38.2% 146,139 Other Organic 31.3% 119,876Uncoated Corrugated Cardboard 11.9% 2.9% 45,719 Food 22.4% 5.9% 85,607Paper Bags 0.5% 0.2% 1,870 Leaves & Grass 7.4% 5.2% 28,299Newspaper 2.6% 1.1% 9,852 Prunings & Trimmings 0.1% 0.1% 345White Ledger Paper 3.1% 1.2% 11,867 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.3% 0.1% 1,025 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.6% 0.2% 2,120 Manures 0.0% 0.0% 0Other Office Paper 1.6% 0.5% 6,168 Textiles 0.4% 0.2% 1,419Magazines and Catalogs 3.6% 1.7% 13,686 Remainder/Composite Organic 1.1% 0.4% 4,206Phone Books and Directories 0.2% 0.1% 908Other Miscellaneous Paper 6.2% 2.8% 23,806 Construction & Demolition 5.9% 22,580Remainder/Composite Paper 7.6% 1.3% 29,116 Concrete 0.0% 0.0% 12


Clear Glass Bottles & Containers 1.1% 0.6% 4,167 Lumber 4.4% 1.7% 16,756Green Glass Bottles & Containers 0.1% 0.0% 200 Gypsum Board 0.0% 0.0% 0Brown Glass Bottles & Containers 0.8% 0.6% 2,994 Rock, Soil & Fines 1.5% 1.5% 5,810Other Colored Glass Bottles & Containers 0.0% 0.0% 11 Remainder/Composite C&D 0.0% 0.0% 0Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.0% 0.0% 104 Household Hazardous Waste 0.0% 66


Tin/Steel Cans 0.8% 0.3% 2,875 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.0% 0.0% 66Other Ferrous Metal 1.7% 0.7% 6,459 Remainder/Composite HHW 0.0% 0.0% 0Aluminum Cans 0.1% 0.0% 437Other Non-Ferrous Metal 0.1% 0.0% 345 Special Waste 5.3% 20,367Remainder/Composite Metal 0.6% 0.4% 2,481 Ash 0.0% 0.0% 0


HDPE Containers 0.3% 0.1% 1,320 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.2% 0.1% 919 Bulky Items 0.1% 0.1% 541Miscellaneous Plastic Containers 0.2% 0.1% 844 Tires 0.7% 0.6% 2,716Film Plastic 8.0% 1.4% 30,564 Remainder/Composite Special Waste 4.5% 4.2% 17,109Durable Plastic Items 3.6% 2.3% 13,730Remainder/Composite Plastic 1.3% 0.4% 4,991 Mixed Residue 0.4% 0.1% 1,456



Table 22: Composition of Waste from Group F: Retail Trade - Automotive Dealers & Service Stations


Paper 33.9% 59,497 Other Organic 13.5% 23,727Uncoated Corrugated Cardboard 10.4% 1.6% 18,310 Food 6.1% 1.1% 10,625Paper Bags 0.5% 0.1% 960 Leaves & Grass 3.0% 1.3% 5,320Newspaper 4.8% 1.2% 8,361 Prunings & Trimmings 0.1% 0.1% 149White Ledger Paper 1.6% 0.6% 2,890 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.0% 0.0% 82 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.5% 0.2% 867 Manures 0.0% 0.0% 0Other Office Paper 1.4% 0.4% 2,473 Textiles 0.7% 0.2% 1,183Magazines and Catalogs 0.5% 0.1% 937 Remainder/Composite Organic 3.7% 1.1% 6,450Phone Books and Directories 0.2% 0.1% 386Other Miscellaneous Paper 4.4% 0.6% 7,637 Construction & Demolition 14.9% 26,149Remainder/Composite Paper 9.5% 1.7% 16,593 Concrete 0.7% 0.7% 1,206


Clear Glass Bottles & Containers 1.9% 0.4% 3,260 Lumber 6.1% 3.4% 10,787Green Glass Bottles & Containers 0.3% 0.1% 524 Gypsum Board 0.0% 0.0% 0Brown Glass Bottles & Containers 0.3% 0.1% 477 Rock, Soil & Fines 2.3% 1.6% 3,998Other Colored Glass Bottles & Containers 0.1% 0.0% 142 Remainder/Composite C&D 5.8% 3.9% 10,157Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 1.4% 0.8% 2,481 Household Hazardous Waste 0.2% 430


Tin/Steel Cans 0.7% 0.1% 1,170 Used Oil 0.2% 0.2% 346Major Appliances 0.0% 0.0% 0 Batteries 0.0% 0.0% 84Other Ferrous Metal 8.2% 2.5% 14,452 Remainder/Composite HHW 0.0% 0.0% 0Aluminum Cans 0.3% 0.1% 527Other Non-Ferrous Metal 1.0% 0.4% 1,759 Special Waste 9.5% 16,705Remainder/Composite Metal 3.0% 0.7% 5,185 Ash 0.0% 0.0% 0


HDPE Containers 2.4% 0.5% 4,195 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.7% 0.1% 1,305 Bulky Items 0.0% 0.0% 0Miscellaneous Plastic Containers 0.6% 0.1% 1,005 Tires 9.3% 4.7% 16,248Film Plastic 3.5% 0.5% 6,083 Remainder/Composite Special Waste 0.3% 0.2% 458Durable Plastic Items 2.1% 1.1% 3,671Remainder/Composite Plastic 1.1% 0.2% 2,013 Mixed Residue 0.4% 0.1% 650



Table 23: Composition of Waste from Group G: Services - Other Professional


Paper 40.8% 332,114 Other Organic 38.3% 312,085Uncoated Corrugated Cardboard 3.8% 1.0% 30,986 Food 11.8% 2.3% 95,909Paper Bags 0.5% 0.1% 3,681 Leaves & Grass 19.9% 5.7% 162,003Newspaper 2.9% 0.8% 23,769 Prunings & Trimmings 1.9% 1.1% 15,486White Ledger Paper 5.3% 1.7% 43,207 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 1.0% 0.5% 7,860 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.3% 0.2% 2,750 Manures 0.0% 0.0% 0Other Office Paper 2.0% 0.6% 15,918 Textiles 0.3% 0.1% 2,750Magazines and Catalogs 4.1% 2.1% 33,105 Remainder/Composite Organic 4.4% 1.9% 35,937Phone Books and Directories 0.1% 0.1% 912Other Miscellaneous Paper 5.3% 0.8% 43,548 Construction & Demolition 6.2% 50,500Remainder/Composite Paper 15.5% 2.1% 126,378 Concrete 1.2% 1.1% 9,839


Clear Glass Bottles & Containers 1.4% 0.4% 11,245 Lumber 1.8% 0.9% 14,453Green Glass Bottles & Containers 0.5% 0.4% 3,790 Gypsum Board 0.4% 0.4% 2,970Brown Glass Bottles & Containers 0.3% 0.2% 2,110 Rock, Soil & Fines 2.0% 1.2% 16,020Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 0.8% 0.5% 6,896Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.9% 0.6% 7,194 Household Hazardous Waste 0.4% 3,614


Tin/Steel Cans 0.4% 0.1% 3,077 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.1% 0.0% 530Other Ferrous Metal 0.2% 0.1% 1,544 Remainder/Composite HHW 0.4% 0.4% 3,085Aluminum Cans 0.1% 0.0% 1,146Other Non-Ferrous Metal 0.1% 0.0% 1,196 Special Waste 0.6% 5,149Remainder/Composite Metal 2.0% 1.1% 16,242 Ash 0.2% 0.2% 1,465


HDPE Containers 0.6% 0.2% 5,189 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.4% 0.1% 3,365 Bulky Items 0.1% 0.1% 576Miscellaneous Plastic Containers 0.4% 0.1% 3,281 Tires 0.0% 0.0% 0Film Plastic 2.3% 0.3% 18,568 Remainder/Composite Special Waste 0.4% 0.4% 3,108Durable Plastic Items 2.3% 1.0% 18,842Remainder/Composite Plastic 1.3% 0.3% 10,712 Mixed Residue 0.4% 0.2% 3,580



Table 24: Composition of Waste from Group H: Retail Trade - Food Store


Paper 27.5% 275,717 Other Organic 43.3% 434,383Uncoated Corrugated Cardboard 8.2% 2.0% 82,333 Food 39.8% 5.3% 399,222Paper Bags 0.6% 0.1% 6,258 Leaves & Grass 0.8% 0.5% 8,327Newspaper 2.7% 1.1% 27,118 Prunings & Trimmings 0.2% 0.2% 2,362White Ledger Paper 0.6% 0.4% 6,458 Branches & Stumps 0.3% 0.3% 3,217Colored Ledger Paper 0.0% 0.0% 196 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.2% 0.1% 1,821 Manures 0.0% 0.0% 0Other Office Paper 0.3% 0.1% 3,297 Textiles 0.7% 0.3% 6,564Magazines and Catalogs 0.3% 0.1% 3,337 Remainder/Composite Organic 1.5% 0.9% 14,691Phone Books and Directories 0.1% 0.1% 1,425Other Miscellaneous Paper 2.5% 0.6% 25,044 Construction & Demolition 10.8% 107,955Remainder/Composite Paper 11.8% 1.8% 118,431 Concrete 0.5% 0.5% 5,107


Clear Glass Bottles & Containers 0.9% 0.2% 9,071 Lumber 2.1% 0.8% 21,401Green Glass Bottles & Containers 0.3% 0.2% 3,148 Gypsum Board 7.7% 5.2% 77,176Brown Glass Bottles & Containers 0.2% 0.1% 2,481 Rock, Soil & Fines 0.0% 0.0% 0Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 0.1% 0.1% 1,018Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.1% 0.1% 1,085 Household Hazardous Waste 0.0% 39


Tin/Steel Cans 0.9% 0.3% 9,461 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.0% 0.0% 22Other Ferrous Metal 0.4% 0.2% 3,933 Remainder/Composite HHW 0.0% 0.0% 0Aluminum Cans 0.1% 0.0% 1,274Other Non-Ferrous Metal 0.2% 0.1% 1,576 Special Waste 0.8% 8,257Remainder/Composite Metal 3.0% 2.3% 30,441 Ash 0.0% 0.0% 0


HDPE Containers 1.1% 0.3% 10,586 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.2% 0.1% 2,361 Bulky Items 0.8% 0.8% 8,257Miscellaneous Plastic Containers 0.4% 0.2% 4,346 Tires 0.0% 0.0% 0Film Plastic 7.1% 1.7% 71,358 Remainder/Composite Special Waste 0.0% 0.0% 0Durable Plastic Items 0.5% 0.2% 5,205Remainder/Composite Plastic 1.9% 0.8% 19,459 Mixed Residue 0.1% 0.0% 899



Table 25: Composition of Waste from Group I: Construction


Paper 20.4% 283,064 Other Organic 17.0% 235,671Uncoated Corrugated Cardboard 5.5% 1.4% 76,864 Food 2.5% 0.7% 35,064Paper Bags 0.3% 0.1% 4,103 Leaves & Grass 4.4% 2.3% 60,895Newspaper 3.2% 1.0% 44,524 Prunings & Trimmings 1.8% 1.4% 24,356White Ledger Paper 2.8% 1.4% 38,330 Branches & Stumps 0.0% 0.0% 422Colored Ledger Paper 0.1% 0.1% 1,596 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.0% 0.0% 442 Manures 0.0% 0.0% 0Other Office Paper 0.9% 0.4% 13,122 Textiles 1.8% 0.9% 24,779Magazines and Catalogs 1.0% 0.4% 13,535 Remainder/Composite Organic 6.5% 2.1% 90,155Phone Books and Directories 0.3% 0.2% 4,770Other Miscellaneous Paper 3.2% 0.8% 44,414 Construction & Demolition 39.5% 547,012Remainder/Composite Paper 3.0% 0.9% 41,363 Concrete 1.2% 0.7% 16,055


Clear Glass Bottles & Containers 0.3% 0.1% 4,348 Lumber 16.2% 3.9% 224,459Green Glass Bottles & Containers 0.0% 0.0% 457 Gypsum Board 5.4% 3.1% 74,254Brown Glass Bottles & Containers 0.1% 0.0% 754 Rock, Soil & Fines 5.4% 4.2% 75,401Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 11.3% 4.4% 156,778Flat Glass 1.7% 0.9% 23,663Remainer/Composite Glass 1.8% 1.5% 24,843 Household Hazardous Waste 0.2% 2,668


Tin/Steel Cans 0.4% 0.1% 5,485 Used Oil 0.0% 0.0% 0Major Appliances 0.6% 0.4% 7,705 Batteries 0.1% 0.1% 1,055Other Ferrous Metal 5.4% 1.8% 74,746 Remainder/Composite HHW 0.1% 0.1% 1,614Aluminum Cans 0.1% 0.0% 1,766Other Non-Ferrous Metal 0.4% 0.2% 5,380 Special Waste 4.2% 58,591Remainder/Composite Metal 2.7% 1.2% 37,531 Ash 0.0% 0.0% 0





Table 26: Composition of Waste from Group J: Services - Medical / Health




Clear Glass Bottles & Containers 1.3% 0.2% 26,283 Lumber 0.7% 0.4% 13,762Green Glass Bottles & Containers 0.0% 0.0% 692 Gypsum Board 0.5% 0.4% 11,021Brown Glass Bottles & Containers 0.1% 0.0% 1,797 Rock, Soil & Fines 0.2% 0.1% 3,816Other Colored Glass Bottles & Containers 0.0% 0.0% 601 Remainder/Composite C&D 0.1% 0.0% 2,213Flat Glass 0.0% 0.0% 430Remainer/Composite Glass 0.6% 0.4% 12,900 Household Hazardous Waste 0.2% 3,299




HDPE Containers 0.6% 0.1% 11,411 Treated Medical Waste 0.1% 0.1% 1,840PETE Containers 0.4% 0.1% 7,890 Bulky Items 7.4% 5.7% 150,670Miscellaneous Plastic Containers 0.5% 0.1% 10,848 Tires 0.0% 0.0% 0Film Plastic 3.4% 0.3% 68,564 Remainder/Composite Special Waste 3.0% 1.2% 60,697Durable Plastic Items 1.4% 0.3% 29,229Remainder/Composite Plastic 1.8% 0.3% 37,083 Mixed Residue 0.2% 0.0% 3,354



Table 27: Composition of Waste from Group K: Manufacturing - Printing / Publishing


Paper 66.3% 109,737 Other Organic 7.0% 11,663Uncoated Corrugated Cardboard 9.8% 3.4% 16,221 Food 3.4% 1.2% 5,672Paper Bags 0.7% 0.2% 1,168 Leaves & Grass 0.5% 0.4% 847Newspaper 5.3% 2.6% 8,767 Prunings & Trimmings 0.0% 0.0% 22White Ledger Paper 5.2% 1.5% 8,660 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.8% 0.3% 1,332 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.3% 0.2% 457 Manures 0.0% 0.0% 0Other Office Paper 4.2% 1.2% 7,031 Textiles 1.7% 1.5% 2,870Magazines and Catalogs 12.2% 3.5% 20,202 Remainder/Composite Organic 1.4% 0.5% 2,253Phone Books and Directories 0.3% 0.2% 443Other Miscellaneous Paper 11.7% 3.9% 19,452 Construction & Demolition 7.4% 12,231Remainder/Composite Paper 15.7% 3.9% 26,002 Concrete 0.0% 0.0% 0


Clear Glass Bottles & Containers 0.6% 0.2% 968 Lumber 7.3% 4.1% 12,104Green Glass Bottles & Containers 0.0% 0.0% 43 Gypsum Board 0.0% 0.0% 0Brown Glass Bottles & Containers 0.0% 0.0% 71 Rock, Soil & Fines 0.0% 0.0% 0Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 0.1% 0.1% 127Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.0% 0.0% 17 Household Hazardous Waste 0.5% 870


Tin/Steel Cans 2.1% 0.6% 3,438 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.0% 0.0% 6Other Ferrous Metal 2.7% 1.7% 4,499 Remainder/Composite HHW 0.0% 0.0% 0Aluminum Cans 0.1% 0.0% 87Other Non-Ferrous Metal 0.0% 0.0% 53 Special Waste 2.2% 3,654Remainder/Composite Metal 0.2% 0.1% 274 Ash 0.0% 0.0% 0


HDPE Containers 1.3% 0.9% 2,138 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.1% 0.0% 225 Bulky Items 2.2% 2.1% 3,653Miscellaneous Plastic Containers 0.3% 0.1% 468 Tires 0.0% 0.0% 0Film Plastic 3.2% 0.8% 5,222 Remainder/Composite Special Waste 0.0% 0.0% 1Durable Plastic Items 1.9% 1.1% 3,228Remainder/Composite Plastic 3.6% 2.2% 5,987 Mixed Residue 0.4% 0.2% 724



Table 28: Composition of Waste from Group L: Services - Business Services


Paper 40.8% 414,935 Other Organic 31.1% 315,511Uncoated Corrugated Cardboard 6.7% 1.8% 67,924 Food 6.9% 2.0% 69,825Paper Bags 0.9% 0.2% 9,093 Leaves & Grass 6.4% 5.4% 64,771Newspaper 2.2% 0.5% 22,098 Prunings & Trimmings 0.1% 0.1% 828White Ledger Paper 4.9% 1.2% 50,001 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.3% 0.1% 2,967 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.8% 0.4% 7,969 Manures 0.0% 0.0% 0Other Office Paper 2.0% 0.5% 20,758 Textiles 16.6% 6.6% 169,118Magazines and Catalogs 1.5% 0.5% 15,245 Remainder/Composite Organic 1.1% 0.6% 10,969Phone Books and Directories 0.0% 0.0% 0Other Miscellaneous Paper 7.5% 1.3% 76,146 Construction & Demolition 3.9% 39,673Remainder/Composite Paper 14.1% 3.5% 142,735 Concrete 0.0% 0.0% 482


Clear Glass Bottles & Containers 1.4% 0.4% 14,228 Lumber 2.6% 1.7% 26,159Green Glass Bottles & Containers 1.0% 0.8% 9,781 Gypsum Board 0.3% 0.3% 2,884Brown Glass Bottles & Containers 0.2% 0.1% 1,615 Rock, Soil & Fines 0.7% 0.6% 7,251Other Colored Glass Bottles & Containers 0.0% 0.0% 312 Remainder/Composite C&D 0.3% 0.2% 2,632Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.5% 0.3% 5,473 Household Hazardous Waste 0.7% 7,257







Table 29: Composition of Waste from Group M: Services - Education




Clear Glass Bottles & Containers 1.0% 0.4% 7,394 Lumber 0.3% 0.2% 2,177Green Glass Bottles & Containers 0.0% 0.0% 251 Gypsum Board 0.0% 0.0% 0Brown Glass Bottles & Containers 0.3% 0.2% 2,145 Rock, Soil & Fines 0.0% 0.0% 40Other Colored Glass Bottles & Containers 0.0% 0.0% 124 Remainder/Composite C&D 0.1% 0.1% 800Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.0% 0.0% 249 Household Hazardous Waste 0.1% 640


Tin/Steel Cans 1.2% 0.7% 9,267 Used Oil 0.0% 0.0% 149Major Appliances 0.4% 0.3% 3,353 Batteries 0.1% 0.1% 487Other Ferrous Metal 1.8% 1.1% 13,554 Remainder/Composite HHW 0.0% 0.0% 0Aluminum Cans 0.2% 0.0% 1,499Other Non-Ferrous Metal 0.3% 0.1% 2,131 Special Waste 0.9% 6,691Remainder/Composite Metal 1.2% 0.7% 9,128 Ash 0.0% 0.0% 0





Table 30: Composition of Waste from Group N: Public Administration


Paper 39.4% 109,493 Other Organic 27.7% 77,117Uncoated Corrugated Cardboard 4.6% 0.8% 12,768 Food 9.8% 1.7% 27,299Paper Bags 0.5% 0.1% 1,369 Leaves & Grass 16.1% 5.4% 44,735Newspaper 5.5% 1.1% 15,375 Prunings & Trimmings 0.1% 0.1% 286White Ledger Paper 6.5% 1.5% 18,023 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.4% 0.1% 1,076 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.2% 0.1% 662 Manures 0.0% 0.0% 0Other Office Paper 2.0% 0.4% 5,550 Textiles 1.0% 0.5% 2,662Magazines and Catalogs 1.7% 0.3% 4,602 Remainder/Composite Organic 0.8% 0.3% 2,135Phone Books and Directories 0.2% 0.1% 598Other Miscellaneous Paper 4.1% 0.6% 11,383 Construction & Demolition 12.9% 35,945Remainder/Composite Paper 13.7% 2.2% 38,087 Concrete 7.0% 3.5% 19,351


Clear Glass Bottles & Containers 1.0% 0.2% 2,717 Lumber 5.0% 2.4% 13,915Green Glass Bottles & Containers 0.1% 0.1% 288 Gypsum Board 0.2% 0.2% 691Brown Glass Bottles & Containers 1.5% 1.3% 4,072 Rock, Soil & Fines 0.1% 0.1% 163Other Colored Glass Bottles & Containers 0.0% 0.0% 133 Remainder/Composite C&D 0.7% 0.5% 1,826Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.2% 0.1% 542 Household Hazardous Waste 0.2% 577




HDPE Containers 0.2% 0.0% 549 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.6% 0.1% 1,582 Bulky Items 0.0% 0.0% 0Miscellaneous Plastic Containers 0.6% 0.1% 1,589 Tires 0.0% 0.0% 0Film Plastic 4.4% 1.3% 12,219 Remainder/Composite Special Waste 1.1% 1.1% 3,186Durable Plastic Items 3.6% 1.4% 10,078Remainder/Composite Plastic 1.5% 0.3% 4,165 Mixed Residue 0.2% 0.0% 421



Table 31: Composition of Waste from Group O: Services - Hotels / Lodging


Paper 37.1% 170,737 Other Organic 37.1% 170,437Uncoated Corrugated Cardboard 5.7% 1.0% 26,079 Food 28.0% 3.5% 128,703Paper Bags 0.8% 0.1% 3,572 Leaves & Grass 2.6% 1.5% 12,091Newspaper 12.7% 1.9% 58,412 Prunings & Trimmings 1.7% 1.4% 7,683White Ledger Paper 0.8% 0.2% 3,805 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.1% 0.0% 354 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.7% 0.2% 3,050 Manures 0.0% 0.0% 0Other Office Paper 0.4% 0.1% 2,037 Textiles 2.0% 0.5% 9,079Magazines and Catalogs 1.7% 0.4% 7,935 Remainder/Composite Organic 2.8% 0.5% 12,880Phone Books and Directories 1.1% 0.7% 4,865Other Miscellaneous Paper 4.4% 0.5% 20,137 Construction & Demolition 1.2% 5,590Remainder/Composite Paper 8.8% 0.8% 40,491 Concrete 0.1% 0.1% 425


Clear Glass Bottles & Containers 4.3% 0.8% 19,739 Lumber 0.1% 0.0% 346Green Glass Bottles & Containers 1.6% 0.3% 7,292 Gypsum Board 0.0% 0.0% 0Brown Glass Bottles & Containers 3.5% 0.7% 16,014 Rock, Soil & Fines 0.1% 0.1% 611Other Colored Glass Bottles & Containers 0.0% 0.0% 107 Remainder/Composite C&D 0.9% 0.6% 4,207Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.5% 0.1% 2,130 Household Hazardous Waste 0.0% 107


Tin/Steel Cans 0.7% 0.2% 3,251 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.0% 0.0% 107Other Ferrous Metal 1.4% 0.7% 6,526 Remainder/Composite HHW 0.0% 0.0% 0Aluminum Cans 0.5% 0.1% 2,259Other Non-Ferrous Metal 0.2% 0.0% 854 Special Waste 0.4% 1,786Remainder/Composite Metal 0.4% 0.2% 1,729 Ash 0.0% 0.0% 0


HDPE Containers 0.9% 0.2% 4,310 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.9% 0.1% 4,184 Bulky Items 0.0% 0.0% 0Miscellaneous Plastic Containers 0.6% 0.1% 2,761 Tires 0.4% 0.4% 1,767Film Plastic 4.9% 0.3% 22,328 Remainder/Composite Special Waste 0.0% 0.0% 19Durable Plastic Items 1.3% 0.4% 5,854Remainder/Composite Plastic 1.8% 0.4% 8,478 Mixed Residue 0.7% 0.3% 3,315



Table 32: Composition of Waste from Group P: Trucking & Warehousing


Paper 34.9% 85,443 Other Organic 12.2% 29,790Uncoated Corrugated Cardboard 7.0% 1.3% 17,228 Food 4.0% 1.0% 9,720Paper Bags 1.2% 0.8% 2,978 Leaves & Grass 0.5% 0.4% 1,345Newspaper 2.9% 1.0% 7,001 Prunings & Trimmings 1.8% 1.1% 4,451White Ledger Paper 9.6% 6.0% 23,444 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.1% 0.0% 176 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.7% 0.3% 1,800 Manures 0.0% 0.0% 0Other Office Paper 3.0% 0.8% 7,357 Textiles 0.8% 0.3% 1,889Magazines and Catalogs 1.0% 0.3% 2,549 Remainder/Composite Organic 5.1% 3.5% 12,384Phone Books and Directories 0.3% 0.2% 767Other Miscellaneous Paper 3.3% 0.8% 8,055 Construction & Demolition 23.7% 58,048Remainder/Composite Paper 5.8% 1.5% 14,087 Concrete 4.9% 3.5% 11,992


Clear Glass Bottles & Containers 0.9% 0.3% 2,317 Lumber 13.5% 4.5% 33,049Green Glass Bottles & Containers 0.1% 0.1% 303 Gypsum Board 3.1% 2.4% 7,469Brown Glass Bottles & Containers 0.1% 0.0% 184 Rock, Soil & Fines 0.1% 0.1% 336Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 2.1% 1.8% 5,196Flat Glass 0.5% 0.3% 1,105Remainer/Composite Glass 1.2% 0.8% 2,909 Household Hazardous Waste 0.9% 2,196


Tin/Steel Cans 0.5% 0.1% 1,169 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.0% 0.0% 12Other Ferrous Metal 7.2% 3.9% 17,629 Remainder/Composite HHW 0.9% 0.9% 2,184Aluminum Cans 0.2% 0.1% 525Other Non-Ferrous Metal 0.3% 0.1% 618 Special Waste 6.5% 15,910Remainder/Composite Metal 4.2% 1.6% 10,330 Ash 0.3% 0.3% 649


HDPE Containers 0.7% 0.2% 1,661 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.3% 0.1% 653 Bulky Items 6.2% 3.9% 15,189Miscellaneous Plastic Containers 0.9% 0.5% 2,137 Tires 0.0% 0.0% 0Film Plastic 2.9% 0.9% 7,113 Remainder/Composite Special Waste 0.0% 0.0% 72Durable Plastic Items 0.5% 0.1% 1,296Remainder/Composite Plastic 1.1% 0.3% 2,712 Mixed Residue 0.3% 0.1% 830



Table 33: Composition of Waste from Group Q: Wholesale Trade - Durable Goods




Clear Glass Bottles & Containers 0.5% 0.2% 2,858 Lumber 12.1% 3.5% 68,681Green Glass Bottles & Containers 0.0% 0.0% 279 Gypsum Board 0.0% 0.0% 0Brown Glass Bottles & Containers 0.1% 0.1% 613 Rock, Soil & Fines 0.9% 0.7% 4,951Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 0.1% 0.1% 640Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 1.7% 1.6% 9,606 Household Hazardous Waste 0.1% 444







Table 34: Composition of Waste from Group R: Manufacturing - Other


Paper 28.5% 148,263 Other Organic 17.6% 91,612Uncoated Corrugated Cardboard 6.9% 2.8% 35,666 Food 2.2% 0.7% 11,496Paper Bags 0.4% 0.2% 2,051 Leaves & Grass 4.3% 3.3% 22,317Newspaper 1.2% 0.4% 6,291 Prunings & Trimmings 0.1% 0.1% 560White Ledger Paper 2.2% 1.0% 11,319 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.6% 0.6% 3,306 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.4% 0.2% 1,903 Manures 0.0% 0.0% 0Other Office Paper 0.5% 0.1% 2,639 Textiles 4.0% 2.0% 20,692Magazines and Catalogs 3.0% 1.8% 15,439 Remainder/Composite Organic 7.0% 2.5% 36,548Phone Books and Directories 0.6% 0.4% 3,298Other Miscellaneous Paper 4.1% 1.6% 21,575 Construction & Demolition 17.9% 92,958Remainder/Composite Paper 8.6% 1.8% 44,775 Concrete 0.3% 0.2% 1,382


Clear Glass Bottles & Containers 0.3% 0.1% 1,570 Lumber 14.7% 4.9% 76,588Green Glass Bottles & Containers 0.0% 0.0% 54 Gypsum Board 1.3% 1.3% 6,986Brown Glass Bottles & Containers 0.0% 0.0% 16 Rock, Soil & Fines 1.1% 0.8% 5,962Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 0.4% 0.2% 1,835Flat Glass 0.2% 0.2% 858Remainer/Composite Glass 1.8% 1.1% 9,493 Household Hazardous Waste 0.0% 180




HDPE Containers 0.4% 0.1% 1,865 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.2% 0.0% 864 Bulky Items 0.5% 0.5% 2,552Miscellaneous Plastic Containers 0.3% 0.2% 1,786 Tires 1.0% 1.0% 5,215Film Plastic 2.9% 0.9% 15,010 Remainder/Composite Special Waste 6.8% 3.8% 35,145Durable Plastic Items 11.4% 4.2% 59,304Remainder/Composite Plastic 2.4% 1.2% 12,356 Mixed Residue 1.6% 1.0% 8,242



Table 35: Composition of Waste from Group S: Transportation - Other


Paper 44.6% 90,095 Other Organic 13.2% 26,622Uncoated Corrugated Cardboard 6.7% 1.5% 13,580 Food 7.0% 1.3% 14,097Paper Bags 0.9% 0.2% 1,781 Leaves & Grass 1.1% 0.6% 2,301Newspaper 6.9% 2.1% 13,870 Prunings & Trimmings 0.0% 0.0% 0White Ledger Paper 4.6% 1.0% 9,332 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.3% 0.1% 512 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 1.0% 0.3% 2,046 Manures 0.0% 0.0% 0Other Office Paper 6.1% 1.7% 12,429 Textiles 0.6% 0.2% 1,270Magazines and Catalogs 2.2% 0.5% 4,469 Remainder/Composite Organic 4.4% 1.3% 8,954Phone Books and Directories 0.2% 0.1% 312Other Miscellaneous Paper 3.3% 0.5% 6,757 Construction & Demolition 16.6% 33,564Remainder/Composite Paper 12.4% 1.5% 25,008 Concrete 0.0% 0.0% 0


Clear Glass Bottles & Containers 1.2% 0.3% 2,526 Lumber 11.0% 3.5% 22,186Green Glass Bottles & Containers 0.5% 0.3% 974 Gypsum Board 4.0% 2.9% 8,084Brown Glass Bottles & Containers 0.2% 0.1% 334 Rock, Soil & Fines 0.1% 0.1% 268Other Colored Glass Bottles & Containers 0.0% 0.0% 2 Remainder/Composite C&D 1.5% 0.9% 3,026Flat Glass 0.2% 0.2% 432Remainer/Composite Glass 2.1% 1.6% 4,173 Household Hazardous Waste 0.1% 123


Tin/Steel Cans 0.4% 0.1% 779 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.1% 0.0% 123Other Ferrous Metal 2.4% 1.0% 4,899 Remainder/Composite HHW 0.0% 0.0% 1Aluminum Cans 0.3% 0.1% 599Other Non-Ferrous Metal 0.3% 0.1% 576 Special Waste 0.2% 305Remainder/Composite Metal 3.0% 1.4% 5,998 Ash 0.1% 0.1% 207


HDPE Containers 0.3% 0.1% 616 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.6% 0.1% 1,162 Bulky Items 0.0% 0.0% 59Miscellaneous Plastic Containers 0.6% 0.1% 1,270 Tires 0.0% 0.0% 0Film Plastic 8.5% 2.5% 17,283 Remainder/Composite Special Waste 0.0% 0.0% 40Durable Plastic Items 1.2% 0.4% 2,364Remainder/Composite Plastic 1.5% 0.3% 2,972 Mixed Residue 2.2% 1.1% 4,486



Table 36: Composition of Waste from Group T: Manufacturing - Electronic Equipment


Paper 41.9% 57,045 Other Organic 10.8% 14,723Uncoated Corrugated Cardboard 6.6% 1.1% 9,013 Food 6.4% 1.1% 8,664Paper Bags 0.9% 0.2% 1,253 Leaves & Grass 1.2% 0.6% 1,600Newspaper 3.3% 0.6% 4,474 Prunings & Trimmings 0.0% 0.0% 29White Ledger Paper 4.6% 1.0% 6,227 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.1% 0.0% 142 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.7% 0.2% 887 Manures 0.0% 0.0% 0Other Office Paper 1.2% 0.4% 1,674 Textiles 0.8% 0.3% 1,092Magazines and Catalogs 3.5% 1.9% 4,768 Remainder/Composite Organic 2.4% 1.1% 3,339Phone Books and Directories 0.2% 0.2% 239Other Miscellaneous Paper 4.4% 0.9% 5,935 Construction & Demolition 13.1% 17,821Remainder/Composite Paper 16.5% 2.9% 22,434 Concrete 3.1% 2.8% 4,228


Clear Glass Bottles & Containers 1.6% 0.4% 2,224 Lumber 5.1% 2.1% 6,960Green Glass Bottles & Containers 0.2% 0.1% 243 Gypsum Board 1.8% 1.6% 2,428Brown Glass Bottles & Containers 0.2% 0.1% 326 Rock, Soil & Fines 0.5% 0.3% 682Other Colored Glass Bottles & Containers 0.0% 0.0% 53 Remainder/Composite C&D 2.6% 1.7% 3,522Flat Glass 0.2% 0.2% 298Remainer/Composite Glass 1.2% 0.7% 1,682 Household Hazardous Waste 0.3% 358




HDPE Containers 0.8% 0.2% 1,053 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.4% 0.1% 569 Bulky Items 0.7% 0.7% 991Miscellaneous Plastic Containers 0.8% 0.3% 1,071 Tires 0.0% 0.0% 23Film Plastic 8.5% 2.2% 11,610 Remainder/Composite Special Waste 0.5% 0.3% 656Durable Plastic Items 2.7% 1.0% 3,729Remainder/Composite Plastic 3.8% 0.7% 5,139 Mixed Residue 0.8% 0.2% 1,057



Table 37: Composition of Waste from Group U: Manufacturing - Food / Kindred


Paper 36.3% 86,580 Other Organic 28.6% 68,178Uncoated Corrugated Cardboard 5.9% 1.2% 14,156 Food 22.4% 4.5% 53,533Paper Bags 0.9% 0.3% 2,252 Leaves & Grass 0.0% 0.0% 0Newspaper 0.8% 0.2% 1,799 Prunings & Trimmings 0.5% 0.4% 1,112White Ledger Paper 1.3% 0.6% 3,130 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.3% 0.3% 776 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.2% 0.1% 396 Manures 0.0% 0.0% 0Other Office Paper 0.7% 0.3% 1,715 Textiles 4.8% 3.9% 11,466Magazines and Catalogs 1.9% 1.6% 4,608 Remainder/Composite Organic 0.9% 0.3% 2,066Phone Books and Directories 1.0% 0.9% 2,480Other Miscellaneous Paper 4.6% 1.0% 11,000 Construction & Demolition 7.9% 18,773Remainder/Composite Paper 18.5% 4.4% 44,269 Concrete 0.6% 0.6% 1,536


Clear Glass Bottles & Containers 0.8% 0.2% 1,793 Lumber 6.5% 2.1% 15,397Green Glass Bottles & Containers 0.0% 0.0% 98 Gypsum Board 0.7% 0.6% 1,655Brown Glass Bottles & Containers 0.3% 0.2% 620 Rock, Soil & Fines 0.0% 0.0% 60Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 0.1% 0.0% 125Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.1% 0.1% 236 Household Hazardous Waste 0.0% 110




HDPE Containers 1.1% 0.5% 2,680 Treated Medical Waste 0.3% 0.3% 811PETE Containers 0.5% 0.2% 1,133 Bulky Items 0.0% 0.0% 0Miscellaneous Plastic Containers 0.2% 0.1% 549 Tires 0.0% 0.0% 0Film Plastic 12.5% 2.1% 29,860 Remainder/Composite Special Waste 1.3% 1.2% 3,187Durable Plastic Items 1.3% 0.6% 3,162Remainder/Composite Plastic 3.1% 1.2% 7,433 Mixed Residue 0.2% 0.1% 567



Table 38: Composition of Waste from Group V: Manufacturing - Lumber & Wood Products


Paper 16.3% 17,486 Other Organic 22.3% 23,959Uncoated Corrugated Cardboard 4.5% 1.4% 4,806 Food 1.3% 0.4% 1,401Paper Bags 0.4% 0.2% 444 Leaves & Grass 0.4% 0.3% 382Newspaper 0.5% 0.2% 515 Prunings & Trimmings 0.2% 0.2% 218White Ledger Paper 1.0% 0.4% 1,049 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.1% 0.0% 76 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.0% 0.0% 37 Manures 0.0% 0.0% 0Other Office Paper 1.0% 0.4% 1,026 Textiles 0.6% 0.2% 634Magazines and Catalogs 0.9% 0.3% 975 Remainder/Composite Organic 19.9% 5.8% 21,325Phone Books and Directories 0.3% 0.2% 293Other Miscellaneous Paper 3.8% 1.6% 4,047 Construction & Demolition 44.1% 47,314Remainder/Composite Paper 3.9% 1.0% 4,217 Concrete 0.0% 0.0% 0


Clear Glass Bottles & Containers 0.4% 0.1% 477 Lumber 34.7% 5.9% 37,197Green Glass Bottles & Containers 0.3% 0.2% 271 Gypsum Board 0.0% 0.0% 0Brown Glass Bottles & Containers 0.1% 0.0% 64 Rock, Soil & Fines 2.1% 1.9% 2,233Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 7.4% 4.8% 7,884Flat Glass 0.0% 0.0% 0Remainer/Composite Glass 0.7% 0.5% 744 Household Hazardous Waste 0.4% 381


Tin/Steel Cans 0.7% 0.2% 761 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.0% 0.0% 3Other Ferrous Metal 5.7% 2.6% 6,165 Remainder/Composite HHW 0.0% 0.0% 0Aluminum Cans 0.1% 0.0% 74Other Non-Ferrous Metal 0.3% 0.2% 331 Special Waste 1.8% 1,893Remainder/Composite Metal 3.2% 2.0% 3,468 Ash 0.0% 0.0% 0

Sewage Solids 0.0% 0.0% 0Plastic 3.0% 3,256 Industrial Sludge 1.2% 1.1% 1,294

HDPE Containers 0.3% 0.2% 369 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.2% 0.0% 163 Bulky Items 0.5% 0.5% 588Miscellaneous Plastic Containers 0.1% 0.0% 144 Tires 0.0% 0.0% 0Film Plastic 1.2% 0.3% 1,239 Remainder/Composite Special Waste 0.0% 0.0% 11Durable Plastic Items 0.8% 0.3% 870Remainder/Composite Plastic 0.4% 0.1% 471 Mixed Residue 0.6% 0.2% 611



Table 39: Composition of Waste from Group W: Manufacturing - Transportation Equipment


Paper 43.0% 22,622 Other Organic 12.4% 6,513Uncoated Corrugated Cardboard 10.0% 1.9% 5,268 Food 4.5% 0.8% 2,373Paper Bags 0.9% 0.3% 476 Leaves & Grass 0.1% 0.1% 61Newspaper 2.7% 0.6% 1,406 Prunings & Trimmings 1.0% 0.8% 519White Ledger Paper 4.5% 1.6% 2,374 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.0% 0.0% 21 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 1.0% 0.6% 542 Manures 0.0% 0.0% 0Other Office Paper 3.0% 1.3% 1,572 Textiles 3.6% 1.7% 1,881Magazines and Catalogs 2.3% 0.6% 1,185 Remainder/Composite Organic 3.2% 1.6% 1,680Phone Books and Directories 0.9% 0.8% 473Other Miscellaneous Paper 5.2% 1.5% 2,761 Construction & Demolition 17.4% 9,157Remainder/Composite Paper 12.4% 2.0% 6,546 Concrete 0.0% 0.0% 0

Asphalt Paving 0.0% 0.0% 0Glass 1.3% 664 Asphalt Roofing 0.0% 0.0% 9

Clear Glass Bottles & Containers 1.0% 0.2% 516 Lumber 14.7% 4.0% 7,715Green Glass Bottles & Containers 0.1% 0.1% 58 Gypsum Board 0.0% 0.0% 0Brown Glass Bottles & Containers 0.0% 0.0% 5 Rock, Soil & Fines 2.4% 2.2% 1,256Other Colored Glass Bottles & Containers 0.0% 0.0% 4 Remainder/Composite C&D 0.3% 0.2% 177Flat Glass 0.1% 0.0% 26Remainer/Composite Glass 0.1% 0.1% 53 Household Hazardous Waste 1.0% 528


Tin/Steel Cans 0.4% 0.1% 220 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.1% 0.1% 54Other Ferrous Metal 4.8% 1.9% 2,550 Remainder/Composite HHW 0.9% 0.8% 450Aluminum Cans 0.2% 0.0% 111Other Non-Ferrous Metal 1.3% 0.8% 688 Special Waste 2.0% 1,055Remainder/Composite Metal 1.2% 0.8% 652 Ash 0.0% 0.0% 0


HDPE Containers 0.4% 0.1% 186 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.4% 0.1% 220 Bulky Items 1.2% 1.1% 609Miscellaneous Plastic Containers 0.3% 0.1% 172 Tires 0.0% 0.0% 0Film Plastic 5.1% 1.0% 2,683 Remainder/Composite Special Waste 0.8% 0.8% 446Durable Plastic Items 3.9% 2.1% 2,054Remainder/Composite Plastic 3.0% 0.7% 1,561 Mixed Residue 1.9% 0.8% 978



Table 40: Composition of Waste from Group X: Retail Trade - Building Material & Garden


Paper 21.4% 95,517 Other Organic 15.0% 67,182Uncoated Corrugated Cardboard 10.3% 4.4% 46,104 Food 1.7% 0.6% 7,681Paper Bags 1.0% 0.3% 4,355 Leaves & Grass 6.4% 3.1% 28,500Newspaper 1.0% 0.2% 4,510 Prunings & Trimmings 0.5% 0.2% 2,394White Ledger Paper 1.0% 0.6% 4,606 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.1% 0.0% 348 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.2% 0.1% 924 Manures 3.0% 2.7% 13,184Other Office Paper 1.1% 0.2% 4,974 Textiles 0.2% 0.1% 924Magazines and Catalogs 0.6% 0.2% 2,636 Remainder/Composite Organic 3.2% 1.3% 14,499Phone Books and Directories 0.0% 0.0% 128Other Miscellaneous Paper 2.9% 0.6% 12,855 Construction & Demolition 38.5% 171,970Remainder/Composite Paper 3.2% 0.7% 14,077 Concrete 5.1% 2.9% 22,610

Asphalt Paving 0.0% 0.0% 0Glass 8.4% 37,374 Asphalt Roofing 0.4% 0.4% 1,733

Clear Glass Bottles & Containers 0.5% 0.1% 2,126 Lumber 16.3% 3.7% 72,624Green Glass Bottles & Containers 0.0% 0.0% 208 Gypsum Board 2.7% 2.3% 12,196Brown Glass Bottles & Containers 0.0% 0.0% 95 Rock, Soil & Fines 10.1% 5.1% 45,148Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 4.0% 1.9% 17,658Flat Glass 1.3% 1.1% 5,926Remainer/Composite Glass 6.5% 4.5% 29,018 Household Hazardous Waste 0.0% 28







Table 41: Composition of Waste from Group Y: Manufacturing - Industrial / Machinery


Paper 36.9% 17,051 Other Organic 12.8% 5,898Uncoated Corrugated Cardboard 9.5% 1.6% 4,389 Food 3.0% 0.6% 1,387Paper Bags 0.9% 0.2% 429 Leaves & Grass 2.2% 0.9% 1,032Newspaper 2.9% 0.6% 1,332 Prunings & Trimmings 0.0% 0.0% 15White Ledger Paper 2.8% 0.6% 1,279 Branches & Stumps 1.6% 1.4% 735Colored Ledger Paper 0.1% 0.0% 38 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 2.1% 1.6% 966 Manures 0.0% 0.0% 0Other Office Paper 1.2% 0.3% 553 Textiles 1.4% 0.5% 623Magazines and Catalogs 1.5% 0.4% 695 Remainder/Composite Organic 4.6% 2.0% 2,106Phone Books and Directories 1.0% 0.5% 482Other Miscellaneous Paper 6.8% 2.2% 3,149 Construction & Demolition 12.2% 5,647Remainder/Composite Paper 8.1% 1.4% 3,739 Concrete 2.1% 1.8% 965

Asphalt Paving 0.0% 0.0% 0Glass 1.4% 665 Asphalt Roofing 0.0% 0.0% 9

Clear Glass Bottles & Containers 1.1% 0.3% 504 Lumber 8.7% 2.1% 4,033Green Glass Bottles & Containers 0.1% 0.0% 34 Gypsum Board 0.0% 0.0% 0Brown Glass Bottles & Containers 0.2% 0.1% 91 Rock, Soil & Fines 0.8% 0.7% 373Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 0.6% 0.5% 268Flat Glass 0.0% 0.0% 18Remainer/Composite Glass 0.0% 0.0% 18 Household Hazardous Waste 0.8% 363


Tin/Steel Cans 0.3% 0.1% 150 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.0% 0.0% 6Other Ferrous Metal 10.6% 3.1% 4,873 Remainder/Composite HHW 0.0% 0.0% 0Aluminum Cans 0.2% 0.1% 107Other Non-Ferrous Metal 0.2% 0.1% 79 Special Waste 5.6% 2,576Remainder/Composite Metal 4.7% 2.3% 2,152 Ash 2.0% 1.9% 924


HDPE Containers 0.6% 0.3% 292 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.3% 0.0% 116 Bulky Items 0.4% 0.4% 168Miscellaneous Plastic Containers 0.3% 0.1% 146 Tires 1.8% 1.7% 828Film Plastic 6.5% 1.3% 2,980 Remainder/Composite Special Waste 1.4% 1.4% 656Durable Plastic Items 2.2% 0.6% 1,035Remainder/Composite Plastic 3.8% 1.1% 1,742 Mixed Residue 0.7% 0.2% 300





Paper 41.0% 356,433 Other Organic 15.5% 134,618Uncoated Corrugated Cardboard 6.9% 1.2% 59,650 Food 5.1% 1.1% 44,648Paper Bags 1.0% 0.3% 8,344 Leaves & Grass 1.2% 0.5% 10,102Newspaper 4.4% 1.3% 38,354 Prunings & Trimmings 1.3% 1.1% 10,967White Ledger Paper 3.4% 1.0% 29,321 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.1% 0.0% 652 Agricultural Crop Residues 0.1% 0.1% 810Computer Paper 0.3% 0.1% 2,526 Manures 0.0% 0.0% 0Other Office Paper 2.0% 0.5% 17,340 Textiles 1.4% 0.7% 12,454Magazines and Catalogs 1.3% 0.3% 10,947 Remainder/Composite Organic 6.4% 2.4% 55,637Phone Books and Directories 0.3% 0.2% 2,403Other Miscellaneous Paper 4.6% 1.0% 40,307 Construction & Demolition 12.7% 110,135Remainder/Composite Paper 16.9% 5.6% 146,588 Concrete 0.2% 0.2% 1,610


Clear Glass Bottles & Containers 1.0% 0.3% 8,962 Lumber 10.2% 4.8% 88,214Green Glass Bottles & Containers 0.1% 0.1% 466 Gypsum Board 0.0% 0.0% 0Brown Glass Bottles & Containers 0.1% 0.1% 988 Rock, Soil & Fines 2.0% 1.8% 17,730Other Colored Glass Bottles & Containers 0.0% 0.0% 0 Remainder/Composite C&D 0.3% 0.2% 2,480Flat Glass 0.0% 0.0% 27Remainer/Composite Glass 0.1% 0.1% 921 Household Hazardous Waste 0.1% 691


Tin/Steel Cans 0.7% 0.4% 6,234 Used Oil 0.0% 0.0% 0Major Appliances 0.0% 0.0% 0 Batteries 0.0% 0.0% 281Other Ferrous Metal 1.6% 0.8% 14,200 Remainder/Composite HHW 0.0% 0.0% 330Aluminum Cans 0.3% 0.1% 2,207Other Non-Ferrous Metal 0.1% 0.0% 909 Special Waste 5.8% 49,991Remainder/Composite Metal 2.7% 1.4% 23,121 Ash 0.0% 0.0% 0


HDPE Containers 0.6% 0.2% 5,645 Treated Medical Waste 0.0% 0.0% 0PETE Containers 0.4% 0.1% 3,242 Bulky Items 0.0% 0.0% 0Miscellaneous Plastic Containers 2.3% 1.3% 20,079 Tires 0.5% 0.5% 4,521Film Plastic 8.4% 3.6% 73,179 Remainder/Composite Special Waste 5.2% 4.7% 45,470Durable Plastic Items 2.2% 0.6% 19,260Remainder/Composite Plastic 3.4% 1.2% 29,114 Mixed Residue 1.0% 0.2% 8,260


Table 42: Composition of Waste from Groups Z through AM: Lumped Group

3.4 RESIDENTIAL WASTE

The objective of this portion of the study was to characterize California’s residential waste stream at the state level. Residential waste is defined as waste disposed by households that is collected and transported by professional waste haulers. This section presents composition findings for the statewide residential sector as a whole, as well as findings for single-family residential waste and multifamily residential waste. As shown in Table 7 (page 13), the residential sector accounts for approximately 38.1% of California’s municipal solid waste stream. The single-family residential subsector accounts for approximately 28.0%, and the multifamily residential subsector accounts for approximately 10.0%. As with many waste composition studies, this study considered single-family residential waste separately from multifamily residential waste. Multifamily waste is typically collected along with commercial waste, and it becomes impractical to separate the multifamily from the commercial waste for sampling at disposal sites. The present study therefore captured multifamily waste at the point of generation (apartment complexes) through a method that closely resembled the capture of commercial waste samples from generating businesses.

3.4.1 THE OVERALL RESIDENTIAL SECTOR DESCRIPTION OF SAMPLES Samples of single-family residential waste were obtained from randomly selected vehicles at the landfills and transfer stations employed in this study. Samples of multifamily residential waste were collected at multifamily complexes that were selected randomly from within the waste sheds considered in this study. Composition percents and estimated tons for each material were derived separately for the single-family residential and multifamily residential subsectors. The estimates for the two subsectors were then combined, with weighting proportionate to the prevalence of each subsector in the overall waste stream, as revealed by the vehicle surveys. (See Appendix A for a description of the methods used in selecting, sorting, and analyzing samples. See Section A.10 of Appendix A for the methodology of combining data from the single-family residential and multifamily residential subsectors to obtain information about the composition of the whole residential sector.) Tables Table 45 and Table 48 present the numbers of samples that were obtained in each region and each season for single-family residential waste and multifamily residential waste, respectively. In all, 228 samples of residential waste were analyzed (148 single-family and 80 multifamily). OVERALL RESIDENTIAL WASTE COMPOSITION Composition results for residential waste are illustrated in Figure 4 and described in detail in Table 44. The broad material class Other Organic Waste accounts for approximately 45% of disposed residential waste, and the broad class Paper accounts more than a quarter of it. (See Table 44 for lists of materials belonging to each class, and see Appendix B for definitions of the materials.)



Figure 4: Overview of Overall Residential Waste

Paper27.4%

Glass4.0%

Metal4.6%

stic8%


4.5%

Mixed Residue4.0%

Household Hazardous

0.3%

Other Organic45.0%

Pla8.

Special1.2%

Food, a component of Other Organic Waste, is the single most prevalent material in residential waste, comprising 20.0%. Leaves and Grass and Remainder/Composite Organic materials also are prevalent, representing 10.5% and 9.5% of the sector’s waste, respectively. In all, materials from the Other Organic Waste and Paper classes comprise eight of the top ten materials in this subsector. Table 43 presents the materials that account for approximately 73% of residential waste. (See Appendix B for definitions of the materials.) Table 44 presents the detailed composition results for the residential sector.

Material Type Est. Pct. Est. Tons Cumulative Pct. Food 20.0% 2,705,226 20.0% Leaves & Grass 10.5% 1,417,730 30.5% Remainder/Composite Organic 9.5% 1,282,074 40.0% Remainder/Composite Paper 8.1% 1,090,003 48.0% Newspaper 6.5% 880,581 54.5% Other Miscellaneous Paper 4.8% 644,372 59.3% Film Plastic 4.2% 570,893 63.5% Mixed Residue 4.0% 541,223 67.5% Uncoated Corrugated Cardboard 3.0% 403,930 70.5% Prunings & Trimmings 2.5% 342,644 73.0%


Table 43: Most Prevalent Materials in Overall Residential Waste



Paper 27.4% 3,712,747 Other Organic 45.0% 6,086,136Uncoated Corrugated Cardboard 3.0% 0.2% 403,930 Food 20.0% 0.8% 2,705,226Paper Bags 1.0% 0.1% 130,225 Leaves & Grass 10.5% 1.3% 1,417,730Newspaper 6.5% 0.6% 880,581 Prunings & Trimmings 2.5% 0.6% 342,644White Ledger Paper 0.6% 0.1% 80,509 Branches & Stumps 0.1% 0.0% 7,301Colored Ledger Paper 0.1% 0.0% 8,821 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.0% 0.0% 4,763 Manures 0.0% 0.0% 0Other Office Paper 1.1% 0.1% 144,021 Textiles 2.4% 0.2% 331,161Magazines and Catalogs 2.0% 0.2% 268,365 Remainder/Composite Organic 9.5% 0.6% 1,282,074Phone Books and Directories 0.4% 0.1% 57,158Other Miscellaneous Paper 4.8% 0.2% 644,372 Construction & Demolition 4.5% 605,744Remainder/Composite Paper 8.1% 0.3% 1,090,003 Concrete 0.2% 0.1% 29,554

Asphalt Paving 0.0% 0.0% 2,756Glass 4.0% 545,888 Asphalt Roofing 0.0% 0.0% 1,832



Tin/Steel Cans 1.4% 0.1% 185,073 Used Oil 0.0% 0.0% 509Major Appliances 0.0% 0.0% 0 Batteries 0.1% 0.0% 10,255Other Ferrous Metal 1.1% 0.2% 153,360 Remainder/Composite HHW 0.0% 0.0% 3,262Aluminum Cans 0.4% 0.0% 50,714Other Non-Ferrous Metal 0.3% 0.0% 38,764 Special Waste 1.2% 167,735Remainder/Composite Metal 1.5% 0.3% 197,889 Ash 0.1% 0.0% 7,933


HDPE Containers 1.1% 0.1% 149,363 Treated Medical Waste 0.0% 0.0% 715PETE Containers 0.6% 0.0% 83,734 Bulky Items 0.4% 0.2% 55,607Miscellaneous Plastic Containers 0.8% 0.1% 109,747 Tires 0.3% 0.2% 36,607Film Plastic 4.2% 0.2% 570,893 Remainder/Composite Special Waste 0.5% 0.1% 66,873Durable Plastic Items 1.0% 0.1% 132,292Remainder/Composite Plastic 1.1% 0.1% 150,486 Mixed Residue 4.0% 0.4% 541,223


Table 44: Composition of Overall Residential Waste

3.4.2 SINGLE-FAMILY RESIDENTIAL WASTE The objective of this portion of the study was to characterize California’s single-family residential waste stream at the state level. This sector includes waste that is collected by haulers from single-family residences. DESCRIPTION OF SAMPLES Samples of single-family residential waste were obtained from randomly selected vehicles at the landfills and transfer stations employed in this study. Approximately 30 samples were obtained from each of the five regions of the state, and approximately six samples were obtained from each disposal facility that was visited. (See Appendix A for a description of the methods used in selecting, sorting, and analyzing samples.) Table 45 presents the numbers of samples that were obtained in each region and each season. For the whole state, 148 samples of single-family residential were sorted (69 in the winter and 79 in the summer).

Table 45: Single-Family Residential Samples Obtained, by Region and Season

Coastal Bay Area Southern Mountain Central Totals Winter 12 11 16 18 12 69 Summer 17 19 11 12 20 79 Totals 29 30 27 30 32 148

Sampling was conducted at five disposal facilities in each region of the state. See Table 71 for the names and locations of the disposal facilities that were visited.

SINGLE-FAMILY RESIDENTIAL WASTE COMPOSITION Composition results for single-family residential waste are illustrated in Figure 5 and described in detail in Table 47. Notably, the broad material class Other Organic Waste accounts for nearly half of disposed single-family residential waste, and the broad class Paper accounts for more than a quarter of it. (See Table 47 for lists of materials belonging to each class, and see Appendix B for definitions of the materials.)


Figure 5: Overview of Single-Family Residential Waste

Paper26.3%

Glass3.1%

Metal4.3%

Plastic8.7%


5.5%

Mixed Residue5.1%

Household Hazardous

0.3%

Other Organic45.7%

Special0.8%

Food, a component of the Organics class, is the single most prevalent material in single-family residential waste, comprising 17.4%. It is followed by Leaves and Grass (12.7%), which is also part of the Organics class. Remainder/Composite Paper (8.2%) and Newspaper (5.2%), both components of the Paper class, also were present in relatively large amounts. Table 46 presents the materials that account for approximately 75% of single-family residential waste. (See Appendix B for definitions of the materials.) Table 47 presents the detailed composition results for the single-family residential sector.



Table 46: Most Prevalent Materials in Single-Family Residential Waste

Material Type Est. Pct. Est. Tons Cumulative Pct. Food 17.4% 1,733,702 17.4% Leaves & Grass 12.7% 1,269,149 30.2% Remainder/Composite Organic 9.5% 945,543 39.7% Remainder/Composite Paper 8.2% 815,931 47.9% Newspaper 5.2% 519,477 53.1% Mixed Residue 5.1% 512,342 58.2% Other Miscellaneous Paper 4.6% 459,418 62.8% Film Plastic 4.2% 419,097 67.0% Prunings & Trimmings 3.3% 330,834 70.4% Uncoated Corrugated Cardboard 3.0% 294,541 73.3%


During sorting, visual observations were made on the Leaves and Grass material type to estimate the portion of the category that each represented. For single-family residential waste, grass was estimated to be 57 percent, and leaves were estimated to be 43 percent of the Leaves and Grass category by weight. These should be considered rough estimates, and no statistical treatment was applied to the breakdown of Leaves and Grass into its two components.



Paper 26.3% 2,618,976 Other Organic 45.7% 4,547,610Uncoated Corrugated Cardboard 3.0% 0.3% 294,541 Food 17.4% 0.9% 1,733,702Paper Bags 1.0% 0.1% 96,823 Leaves & Grass 12.7% 1.7% 1,269,149Newspaper 5.2% 0.6% 519,477 Prunings & Trimmings 3.3% 0.8% 330,834White Ledger Paper 0.6% 0.1% 64,330 Branches & Stumps 0.1% 0.1% 7,302Colored Ledger Paper 0.1% 0.0% 6,927 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.0% 0.0% 4,328 Manures 0.0% 0.0% 0Other Office Paper 1.3% 0.1% 124,788 Textiles 2.6% 0.3% 261,080Magazines and Catalogs 2.0% 0.2% 202,656 Remainder/Composite Organic 9.5% 0.8% 945,543Phone Books and Directories 0.3% 0.1% 29,756Other Miscellaneous Paper 4.6% 0.2% 459,418 Construction & Demolition 5.5% 551,449Remainder/Composite Paper 8.2% 0.4% 815,931 Concrete 0.3% 0.1% 29,557




Tin/Steel Cans 1.4% 0.1% 137,740 Used Oil 0.0% 0.0% 455Major Appliances 0.0% 0.0% 0 Batteries 0.1% 0.0% 7,110Other Ferrous Metal 1.0% 0.1% 101,328 Remainder/Composite HHW 0.0% 0.0% 3,062Aluminum Cans 0.4% 0.0% 35,498Other Non-Ferrous Metal 0.3% 0.0% 27,430 Special Waste 0.8% 81,664Remainder/Composite Metal 1.3% 0.2% 127,165 Ash 0.0% 0.0% 3,922




Table 47: Composition of Single-Family Residential Waste

3.4.3 MULTIFAMILY RESIDENTIAL WASTE The objective of this portion of the study was to characterize California’s multifamily residential waste stream at the state level. This sector includes waste that is collected by haulers from apartments or condominiums. DESCRIPTION OF SAMPLES Samples of multifamily residential waste were obtained from apartment complexes that were selected randomly from within the waste sheds considered in this study. (See Table 71 for a list of waste sheds.) Eighty samples of multifamily waste were apportioned to the five regions of the state in approximate correlation to the multifamily-dwelling population of each region. (See Appendix A for a description of how multifamily samples were apportioned among regions and chosen within each waste shed, as well as the methods used in capturing and sorting samples of multifamily waste.) Table 48 presents the numbers of samples that were obtained in each region and each season. Of the 80 samples captured statewide, 36 were captured in the winter and 44 in the summer.

Table 48: Multifamily Residential Samples Obtained, by Region and Season


MULTIFAMILY RESIDENTIAL WASTE COMPOSITION Composition results for multifamily residential waste are illustrated in Figure 6 and described in detail in Table 50. Notably, the broad material class Other Organic Waste accounts for approximately 43% of disposed multifamily residential waste, and the broad class Paper accounts for approximately 30% of it. (See Table 50 for lists of materials belonging to each class, and see Appendix B for definitions of the materials.)



Figure 6: Overview of Multifamily Residential Waste

Paper30.6%

Glass6.5%

tal5%


1.5%

Mixed Residue0.8%

Household Hazardous

0.4%

Other Organic43.1%

Me5.

Plastic9.1%

Special2.4%

Food, a component of the Organics class, is the single most prevalent material in multifamily residential waste, comprising 27.2%. It is followed by Newspaper (10.1%), Remainder/ Composite Organic Waste (9.4%), and Remainder/Composite Paper (7.7%). Materials in the Organics and Paper classes comprise seven of the top ten materials in multifamily residential waste. Table 49 presents the materials that account for approximately 76% of multifamily residential waste. (See Appendix B for definitions of the materials.) Table 50 presents the detailed composition results for the multifamily residential sector.

Material Type Est. Pct. Est. Tons Cumulative Pct. Food 27.2% 971,463 27.2% Newspaper 10.1% 361,069 37.3% Remainder/Composite Organic 9.4% 336,543 46.8% Remainder/Composite Paper 7.7% 274,086 54.4% Other Miscellaneous Paper 5.2% 184,955 59.6% Film Plastic 4.3% 151,800 63.9% Leaves & Grass 4.2% 148,669 68.0% Clear Glass Bottles & Containers 3.2% 115,203 71.3% Uncoated Corrugated Cardboard 3.1% 109,391 74.3% Remainder/Composite Metal 2.0% 70,719 76.3%


Table 49: Most Prevalent Materials in Multifamily Residential Waste



Paper 30.6% 1,093,767 Other Organic 43.1% 1,538,604Uncoated Corrugated Cardboard 3.1% 0.5% 109,391 Food 27.2% 1.7% 971,463Paper Bags 0.9% 0.1% 33,403 Leaves & Grass 4.2% 1.3% 148,669Newspaper 10.1% 1.4% 361,069 Prunings & Trimmings 0.3% 0.2% 11,839White Ledger Paper 0.5% 0.1% 16,182 Branches & Stumps 0.0% 0.0% 0Colored Ledger Paper 0.1% 0.0% 1,894 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.0% 0.0% 434 Manures 0.0% 0.0% 0Other Office Paper 0.5% 0.1% 19,240 Textiles 2.0% 0.3% 70,090Magazines and Catalogs 1.8% 0.4% 65,713 Remainder/Composite Organic 9.4% 1.1% 336,543Phone Books and Directories 0.8% 0.4% 27,399Other Miscellaneous Paper 5.2% 0.5% 184,955 Construction & Demolition 1.5% 54,335Remainder/Composite Paper 7.7% 0.5% 274,086 Concrete 0.0% 0.0% 0




Tin/Steel Cans 1.3% 0.1% 47,335 Used Oil 0.0% 0.0% 54Major Appliances 0.0% 0.0% 0 Batteries 0.1% 0.0% 3,144Other Ferrous Metal 1.5% 0.5% 52,030 Remainder/Composite HHW 0.0% 0.0% 200Aluminum Cans 0.4% 0.1% 15,216Other Non-Ferrous Metal 0.3% 0.0% 11,334 Special Waste 2.4% 86,059Remainder/Composite Metal 2.0% 0.8% 70,719 Ash 0.1% 0.1% 4,011




Table 50: Composition of Multifamily Residential Waste

3.5 SELF-HAUL WASTE

The objective of this portion of the study was to characterize California’s self-haul waste stream at the state level. Self-haul waste is waste that is transported to the disposal site by someone whose primary business is not waste hauling. This section presents composition findings for the statewide self-haul sector as a whole, as well as findings for commercial self-haul waste and residential self-haul waste. As shown in Table 7 (page 13), the self-haul waste sector accounts for approximately 13.1% of California’s municipal solid waste stream. The commercial self-haul and residential self-haul subsectors make up approximately 10.5% and 2.6% respectively. As part of the vehicle survey, drivers of vehicles carrying commercial self-haul waste to disposal facilities were asked to classify the activity that generated the waste. Based on their responses, it is estimated that commercial self-haul waste from construction and demolition activities represents 4.5% of the overall waste stream. Similarly, waste from roofing and waste from landscaping respectively represent about 1.1% and 0.9% of the overall waste stream. Other miscellaneous commercial activities generate commercial self-haul waste that represents approximately 4.1% of the overall waste stream. These results are shown in Table 9 (page 14).

3.5.1 THE OVERALL SELF-HAUL SECTOR DESCRIPTION OF SAMPLES Samples of self-haul waste were obtained from randomly selected vehicles at the landfills and transfer stations employed in this study. Approximately 50 samples were obtained from each of the five regions of the state, and approximately ten samples were obtained from each disposal facility that was visited. One third of the samples were from residential sources, and two thirds from commercial self-haul sources. Overall self-haul composition results are based on an average of the two subsectors, weighted at the regional level. (See Appendix A for a description of the methods used in selecting, sorting, and analyzing samples.) Table 51 presents the numbers of samples that were obtained in each region and each season. For the whole state, 247 samples of self-haul waste were sorted (118 in the winter and 129 in the summer).

Table 51: Self-Haul Samples Obtained, by Region and Season




OVERALL SELF-HAUL WASTE COMPOSITION Composition results for self-haul waste are illustrated in Figure 7 and described in detail in Table 53. Notably, the broad material class Construction and Demolition Waste accounts for more than half of disposed self-haul waste, as would be expected since a large segment of self-haul tonnage comes from construction, demolition, and roofing activities (see Table 9 on page 14). The broad class Other Organic Waste is the next largest category, accounting for approximately a fifth of self-haul waste. (See Table 53 for lists of materials belonging to each class, and see Appendix B for definitions of the materials.)

Figure 7: Overview of Overall Self-Haul Waste

Metal10.6%

Other Organic20.8%

Glass1.0%

Paper5.5%

Household Hazardous

0.1%

Mixed Residue0.2%


51.3%

Special4.9%

Plastic5.6%

Lumber, a component of the Construction and Demolition Waste class, is the single most prevalent material in self-haul waste, comprising 19.2%. In all, materials from the Construction and Demolition Waste class, the Metals class, and the Other Organics class comprise nine of the top ten materials in this subsector. Table 52 presents the materials that account for approximately 75% of self-haul waste. (See Appendix B for definitions of the materials.) Table 53 presents the detailed composition results for the overall self-haul sector.



Table 52: Most Prevalent Materials in Overall Self-Haul Waste

Material Type Est. Pct. Est. Tons Cumulative Pct. Lumber 19.2% 894,304 19.2% Remainder/Composite Construction & Demolition 10.6% 491,760 29.8% Remainder/Composite Organic 8.2% 379,753 38.0% Other Ferrous Metal 6.7% 312,257 44.7% Concrete 6.7% 311,396 51.4% Gypsum Board 5.5% 254,298 56.8% Prunings & Trimmings 5.4% 250,685 62.2% Asphalt Roofing 5.4% 249,748 67.6% Leaves & Grass 4.0% 185,816 71.6% Bulky Items 3.9% 182,372 75.5%


During sorting, visual observations were made on the Leaves and Grass material type to estimate the portion of the category that each represented in the overall self-haul sector. During the winter, leaves made up 66% of the Leaves and Grass category by weight, and grass made up 34% of the category. During the summer, leaves comprised only 49% of the category, while grass comprised 51%. In self-haul samples from both seasons considered together, leaves represented 54%, and grass represented 46%. These should be considered rough estimates, and no statistical treatment was applied to the breakdown of Leaves and Grass into its two components.



Paper 5.5% 253,949 Other Organic 20.8% 966,563Uncoated Corrugated Cardboard 1.9% 0.3% 89,165 Food 1.1% 0.3% 50,086Paper Bags 0.2% 0.1% 10,000 Leaves & Grass 4.0% 1.4% 185,816Newspaper 0.2% 0.0% 10,768 Prunings & Trimmings 5.4% 1.7% 250,685White Ledger Paper 0.1% 0.0% 3,099 Branches & Stumps 0.9% 0.4% 43,537Colored Ledger Paper 0.0% 0.0% 170 Agricultural Crop Residues 0.0% 0.0% 259Computer Paper 0.0% 0.0% 144 Manures 0.0% 0.0% 0Other Office Paper 0.6% 0.3% 26,444 Textiles 1.2% 0.6% 56,428Magazines and Catalogs 0.2% 0.0% 7,313 Remainder/Composite Organic 8.2% 2.5% 379,753Phone Books and Directories 0.1% 0.0% 2,739Other Miscellaneous Paper 1.3% 0.4% 60,603 Construction & Demolition 51.3% 2,386,666Remainder/Composite Paper 0.9% 0.2% 43,504 Concrete 6.7% 1.7% 311,396




Tin/Steel Cans 0.1% 0.1% 6,607 Used Oil 0.0% 0.0% 411Major Appliances 0.3% 0.2% 15,077 Batteries 0.0% 0.0% 436Other Ferrous Metal 6.7% 1.4% 312,257 Remainder/Composite HHW 0.0% 0.0% 1,138Aluminum Cans 0.0% 0.0% 1,136Other Non-Ferrous Metal 0.3% 0.1% 12,861 Special Waste 4.9% 226,125Remainder/Composite Metal 3.2% 0.9% 147,146 Ash 0.0% 0.0% 1,408


HDPE Containers 0.3% 0.1% 11,753 Treated Medical Waste 0.1% 0.1% 3,007PETE Containers 0.0% 0.0% 2,088 Bulky Items 3.9% 1.2% 182,372Miscellaneous Plastic Containers 0.1% 0.0% 2,860 Tires 0.8% 0.7% 37,037Film Plastic 0.7% 0.1% 33,824 Remainder/Composite Special Waste 0.0% 0.0% 2,300Durable Plastic Items 3.7% 1.1% 173,948Remainder/Composite Plastic 0.7% 0.3% 33,691 Mixed Residue 0.2% 0.1% 11,377


Table 53: Composition of Overall Self-Haul Waste

3.5.2 COMMERCIAL SELF-HAUL WASTE The objective of this portion of the study was to characterize California’s commercial self-haul waste stream at the state level. This sector includes waste hauled to a disposal site by a commercial enterprise, such as a landscaper or contractor, even if the source of waste was residential dwellings. DESCRIPTION OF SAMPLES Samples of commercial self-haul waste were obtained from randomly selected vehicles at the landfills and transfer stations employed in this study. Approximately 32 samples were obtained from each of the five regions of the state, and approximately six samples were obtained from each disposal facility that was visited. (See Appendix A for a description of the methods used in selecting, sorting, and analyzing samples.) Table 54 presents the numbers of samples that were obtained in each region and each season. For the whole state, 162 samples of commercial self-haul waste were sorted (79 in the winter and 83 in the summer).

Table 54: Commercial Self-Haul Samples Obtained, by Region and Season



COMMERCIAL SELF-HAUL WASTE COMPOSITION Composition results for commercial self-haul waste are illustrated in Figure 8 and described in detail in Table 56. The broad material class Construction and Demolition Waste accounts for more than half of disposed commercial self-haul waste, and the broad class Other Organic Waste accounts for a fifth of it. (See Table 56 for lists of materials belonging to each class, and see Appendix B for definitions of the materials.)



Figure 8: Overview of Commercial Self-Haul Waste

Metal10.7%

Other Organic20.0%

Glass0.8%

Paper4.5%

Mixed Residue0.2%


53.5%

Plastic5.5%

Household Hazardous

0.1%

Special4.6%

Lumber, a component of the Construction and Demolition Waste class, is the single most prevalent material in commercial self-haul waste, comprising 19.4%. In all, materials from the Construction and Demolition Waste class, the Metals class, and the Other Organics class (primarily yard waste) comprise nine of the top ten materials in this subsector. Table 55 presents the materials that account for approximately 77% of commercial self-haul waste. (See Appendix B for definitions of the materials.) Table 56 presents the detailed composition results for the commercial self-haul sector.

Material Type Est. Pct. Est. Tons Cumulative Pct. Lumber 19.4% 724,030 19.4% Remainder/Composite Construction & Demolition 11.0% 409,860 30.3% Remainder/Composite Organic 8.2% 306,248 38.5% Concrete 7.1% 265,650 45.6% Other Ferrous Metal 7.0% 260,762 52.6% Gypsum Board 6.0% 226,196 58.6% Asphalt Roofing 6.0% 223,226 64.6% Prunings & Trimmings 5.0% 185,348 69.6% Leaves & Grass 4.0% 150,325 73.6% Durable Plastic Items 3.9% 145,966 77.5%


Table 55: Most Prevalent Materials in Commercial Self-Haul Waste



Paper 4.5% 168,986 Other Organic 20.0% 747,404Uncoated Corrugated Cardboard 1.6% 0.4% 60,833 Food 0.9% 0.9% 33,197Paper Bags 0.2% 0.1% 8,323 Leaves & Grass 4.0% 3.5% 150,325Newspaper 0.2% 0.1% 7,151 Prunings & Trimmings 5.0% 5.1% 185,348White Ledger Paper 0.0% 0.0% 1,427 Branches & Stumps 0.8% 0.9% 31,429Colored Ledger Paper 0.0% 0.0% 74 Agricultural Crop Residues 0.0% 0.0% 0Computer Paper 0.0% 0.0% 15 Manures 0.0% 0.0% 0Other Office Paper 0.3% 0.5% 10,108 Textiles 1.1% 1.5% 40,857Magazines and Catalogs 0.1% 0.1% 3,948 Remainder/Composite Organic 8.2% 5.6% 306,248Phone Books and Directories 0.0% 0.1% 1,716Other Miscellaneous Paper 1.2% 0.9% 46,720 Construction & Demolition 53.5% 1,999,103Remainder/Composite Paper 0.8% 0.3% 28,671 Concrete 7.1% 3.6% 265,650


Clear Glass Bottles & Containers 0.1% 0.1% 3,668 Lumber 19.4% 4.2% 724,030Green Glass Bottles & Containers 0.4% 0.7% 13,150 Gypsum Board 6.0% 2.8% 226,196Brown Glass Bottles & Containers 0.0% 0.0% 779 Rock, Soil & Fines 3.2% 3.1% 120,815Other Colored Glass Bottles & Containers 0.0% 0.0% 20 Remainder/Composite C&D 11.0% 4.0% 409,860Flat Glass 0.2% 0.2% 8,137Remainer/Composite Glass 0.2% 0.3% 5,949 Household Hazardous Waste 0.1% 4,184


Tin/Steel Cans 0.1% 0.1% 4,760 Used Oil 0.0% 0.0% 0Major Appliances 0.4% 0.6% 13,485 Batteries 0.0% 0.0% 189Other Ferrous Metal 7.0% 2.9% 260,762 Remainder/Composite HHW 0.0% 0.0% 487Aluminum Cans 0.0% 0.0% 692Other Non-Ferrous Metal 0.3% 0.1% 10,258 Special Waste 4.6% 170,730Remainder/Composite Metal 3.0% 2.1% 111,678 Ash 0.0% 0.0% 822




Table 56: Composition of Commercial Self-Haul Waste

3.5.3 RESIDENTIAL SELF-HAUL WASTE The objective of this portion of the study was to characterize California’s residential self-haul waste stream at the state level. This sector includes waste that is hauled to a disposal site by a resident from their home. DESCRIPTION OF SAMPLES Samples of residential self-haul waste were obtained from randomly selected vehicles at the landfills and transfer stations employed in this study. Approximately 17 samples were obtained from each of the five regions of the state, and approximately three to four samples were obtained from each disposal facility that was visited. (See Appendix A for a description of the methods used in selecting, sorting, and analyzing samples.) Table 57 presents the numbers of samples that were obtained in each region and each season. For the whole state, 85 samples of residential self-haul waste were sorted (39 in the winter and 46 in the summer).

Table 57: Residential Self-Haul Samples Obtained, by Region and Season



RESIDENTIAL SELF-HAUL WASTE COMPOSITION Composition results for residential self-haul waste are illustrated in Figure 9 and described in detail in Table 59. The broad material class Construction and Demolition Waste accounts for more than one-third of disposed residential self-haul waste, and the broad class Other Organic Waste accounts for a quarter of it. (See Table 59 for lists of materials belonging to each class, and see Appendix B for definitions of the materials.)



Figure 9: Overview of Residential Self-Haul Waste

Metal9.9%

Other Organic26.5%

Glass2.3%

Paper12.3%

Household Hazardous

0.2%

Mixed Residue0.3%


35.8%

Special7.0% Plastic

5.7%

Material Type Est. Pct. Est. Tons Cumulative Pct. Lumber 18.3% 166,415 18.3% Prunings & Trimmings 8.5% 77,642 26.8% Remainder/Composite Organic 8.0% 72,778 34.7% Remainder/Composite Construction & Demolition

7.8% 70,860 42.5%

Bulky Items 5.9% 53,366 48.4% Other Ferrous Metal 4.8% 44,098 53.2% Remainder/Composite Metal 4.4% 40,499 57.7% Uncoated Corrugated Cardboard 4.0% 36,580 61.7% Leaves & Grass 3.8% 34,773 65.5% Concrete 3.7% 34,106 69.2%


Table 58: Most Prevalent Materials in Residential Self-Haul Waste



Paper 12.3% 111,703 Other Organic 26.5% 241,695Uncoated Corrugated Cardboard 4.0% 1.9% 36,580 Food 2.4% 0.9% 22,263Paper Bags 0.2% 0.0% 1,462 Leaves & Grass 3.8% 1.4% 34,773Newspaper 0.5% 0.1% 4,763 Prunings & Trimmings 8.5% 3.5% 77,642White Ledger Paper 0.3% 0.1% 2,480 Branches & Stumps 1.6% 1.6% 14,822Colored Ledger Paper 0.0% 0.0% 144 Agricultural Crop Residues 0.0% 0.0% 418Computer Paper 0.0% 0.0% 204 Manures 0.0% 0.0% 0Other Office Paper 2.7% 2.3% 24,814 Textiles 2.1% 0.6% 18,998Magazines and Catalogs 0.5% 0.2% 4,834 Remainder/Composite Organic 8.0% 1.8% 72,778Phone Books and Directories 0.2% 0.1% 1,392Other Miscellaneous Paper 1.7% 0.5% 15,404 Construction & Demolition 35.8% 326,434Remainder/Composite Paper 2.2% 0.7% 19,625 Concrete 3.7% 1.5% 34,106

Asphalt Paving 0.0% 0.0% 0Glass 2.3% 21,068 Asphalt Roofing 1.0% 0.7% 9,455





HDPE Containers 0.4% 0.1% 4,086 Treated Medical Waste 0.5% 0.5% 4,846PETE Containers 0.1% 0.0% 1,233 Bulky Items 5.9% 1.9% 53,366Miscellaneous Plastic Containers 0.1% 0.0% 1,147 Tires 0.4% 0.3% 3,992Film Plastic 1.5% 0.5% 13,276 Remainder/Composite Special Waste 0.1% 0.1% 775Durable Plastic Items 2.6% 0.6% 23,325Remainder/Composite Plastic 0.9% 0.3% 8,611 Mixed Residue 0.3% 0.1% 2,473


Table 59: Composition of Residential Self-Haul Waste

3.6 RPPC STUDY

3.6.1 INTRODUCTION AND BACKGROUND In 1991 the California legislature passed the Rigid Plastic Packaging Container (RPPC) Act, Senate Bill 235. This act requires all RPPCs sold or offered for sale in California to meet one of the following criteria, if the overall recycling rate of 25% is not met: (1) contain 25% recycled post-consumer content, (2) meet a brand-specific recycling rate, (3) be reusable or refillable five times, or (4) be source-reduced by 10%. This act also requires the CIWMB to calculate an aggregate recycling rate for RPPCs each year. An RPPC is defined by the act as any container that meets ALL of the following criteria:

•

•

•

•

•

•

It is made entirely of plastic, except that caps, lids, and labels may be made of some other material;

It is a packaging container in which a product is sold, offered for sale or distributed in California;

It is capable of maintaining its shape while holding a product;

It is capable of multiple re-closures with an attached or unattached lid or cap;

It contains a minimum of eight fluid ounces but no more than five gallons; and

It is normally used to store a product for at least seven days (i.e., from the time the container is filled).

In 1995 Cascadia Consulting Group was commissioned by the American Plastics Council, working under the direction of the CIWMB, to calculate the aggregated recycling rate for rigid plastic packaging containers. This study was conducted to determine if product manufacturers were in compliance with one of the requirements of Senate Bill 235, the aggregated RPPC recycling rate of at least 25%. For the 1995 study the RPPC recycling rate calculation was expressed as:

Generated RPPCs ofQuantity Recycled RPPCs ofQuantity Rate Recycling RPPC =

The quantity of RPPCs generated was assumed to be equal to the quantity disposed plus the quantity recycled. In order to estimate the quantity of RPPCs disposed, Cascadia conducted an extensive waste characterization study of RPPCs disposed in 1995. Sampling occurred at 24 sites across the state receiving waste from 138 jurisdictions. A total of 889 samples were sorted and weighed. Of those samples, 299 were washed and dried and re-weighed to determine contamination levels. Contamination rates were then calculated for each type of RPPC and for each sector: residential, commercial and self-haul. In the 1995 analysis final estimates of disposed RPPCs were adjusted to compensate for contamination. Dirty “field weights” were adjusted down, using the calculated contamination rates, so that “clean weights” of disposed RPPCs could be compared with clean recycled tonnage, to determine an accurate 1995 RPPC recycling rate.


One of the objectives of California’s 1999 statewide waste composition study was to improve and update the estimate of the amount of disposed RPPCs statewide. This new estimate is to be used in calculating the 1998, 1999 and 2000 RPPC recycling rate.

3.6.2 METHODOLOGY During the course of the 1999 study, dirty “field weights” were recorded for eight categories of RPPCs during the sorting of waste samples. The eight categories of RPPC included in the present study are:

•

•

•

•

•

•

•

•

#1 PET soda bottles

#1 PET custom bottles

#1 PET non-bottle rigids

#2 HDPE natural bottles

#2 HDPE colored bottles

#2 HDPE other containers

All other RPPC bottles

All other RPPC non-bottles The estimated amounts of disposed dirty RPPCs were calculated using the same set of field procedures and the same formulas as for the remainder of the 1999 study. These protocols are documented in Appendix A. As in the 1995 study the dirty “field weights” also included the weight of contaminants such as food, moisture and other non-RPPC materials. To adjust for the additional weight of contaminants in the 1999 data, “clean weights” were calculated using contamination rates derived from the 1995 study. The contamination rates for each type of RPPC and each sector appear in Table 60.

Table 60: Field Weight to Clean Weight Conversion Factors for RPPCs

Contamination Rates (percent of field weight that is contamination)

Commercial Residential Self-Haul #1 PET Soda Bottles 4.63% 10.33% 6.12% #1 PET Custom Bottles 12.51% 13.59% 14.16% #1 PET Non-Bottle Rigids 11.76% 23.49% 13.36% #2 HDPE Natural Bottles 18.03% 11.40% 13.52% #2 HDPE Colored Bottles 17.09% 18.76% 21.90% #2 HDPE Other Containers 26.84% 14.01% 20.77% All Other RPPC Bottles 16.12% 16.20% 15.52% All Other RPPC Non-Bottles 19.52% 23.67% 17.59%

Contamination rates were derived from the 1995 study of RPPC Recycling Rates in California, conducted by Cascadia Consulting Group for the American Plastics Council.


The contamination rates shown in Table 60 were calculated by comparing dirty “field weights” from the 1995 study to the 1995 “clean weights.” First, the sample records from the 1995 study were grouped according to the sector of the waste stream represented (commercial, residential, or self-haul). Then the material categories examined in 1995 were grouped into eight categories that matched the set of RPPC materials considered in the current study. For each of the eight RPPC categories, the sum of all clean weights among the samples was subtracted from the sum of all dirty weights, and the contamination rate was calculated. This process was done separately for each RPPC material in each of the commercial, residential, and self-haul sets of data. The derived contamination rates were used to reduce the field weights of RPPC materials that were recorded in the current study. The difference between 1999 field weights and the derived 1999 clean weights was assumed to be contamination and was added to the material category All Non-RPPC Materials which appears in Table 61 through Table 64. The 1995 contamination rates for self-haul RPPCs were applied to both residential self-haul and commercial self-haul records in the current study. Likewise, the 1995 contamination rates for residential RPPCs were applied to both single-family residential and multifamily residential records in the current study. For a detailed description of the calculations used in the 1995 study to estimate “field” and dry or “clean weights” please see Appendix I. For a description of the statistical procedures used to estimate the percent composition of RPPCs in each sector, see Appendix A.

3.6.3 RESULTS The objective of the RPPC portion of California's statewide waste characterization study was to determine the total amount of RPPCs disposed in the municipal solid waste stream. RPPC disposal data for the overall waste stream are presented below. Estimates of RPPC disposal for the commercial, residential, and self-haul sectors are found in Table 61 through Table 64. OVERALL RPPC DISPOSAL In 1999 an estimated 377,010 tons of RPPCs were disposed in California's municipal waste, representing an estimated 1.06% of the municipal waste stream.5 This represents an increase of 0.35% over the 1995 estimate of 0.71%. The confidence interval for 1999 is +/- 0.07%. This means that we are 90% sure that the true mean or average of RPPCs in California solid waste is between 0.99% and 1.13%. This translates to an overall disposal estimate that ranges from 351,801 tons to 401,551 tons. Overall RPPC disposal estimates for each of the eight categories appear in Table 61.

5 As with all tonnage figures reported in this study, RPPC tonnages were derived by applying 1999 waste composition findings to 1998 tonnages found in California’s Disposal Reporting System.


Table 61: RPPC Composition of Overall Waste Stream

Estimated Percent

+/-

Estimated Tons

#1 PET Soda Bottles 0.12% 0.02% 41,094 #1 PET Custom Bottles 0.24% 0.02% 85,002 #1 PET Non-Bottle Rigids 0.02% 0.01% 5,570 #2 HDPE Natural Bottles 0.25% 0.02% 90,208 #2 HDPE Colored Bottles 0.20% 0.02% 69,338 #2 HDPE Other Containers 0.13% 0.03% 45,991 All Other RPPC Bottles 0.03% 0.01% 11,905 All Other RPPC Non-Bottles 0.08% 0.03% 27,901

Subtotal 1.06% 0.07% 377,010

All Non-RPPC Materials 98.94% 0.07% 35,158,443

Total 100.00% 35,535,453

Confidence intervals calculated at the 90% confidence level. Percentages for materials may not total 100% due to rounding.

COMMERCIAL RPPC DISPOSAL RPPCs comprised an estimated 0.92% of commercial sector waste. This is higher than the 1995 estimate of .71%. Data for individual categories of commercially disposed RPPCs appear in Table 62.

Table 62: RPPC Composition for Commercial Waste

Estimated Percent

+/-

Estimated Tons

#1 PET Soda Bottles 0.12% 0.04% 20,430 #1 PET Custom Bottles 0.23% 0.05% 40,646 #1 PET Non-Bottle Rigids 0.00% 0.00% 670 #2 HDPE Natural Bottles 0.20% 0.03% 35,239 #2 HDPE Colored Bottles 0.16% 0.04% 27,969 #2 HDPE Other Containers 0.11% 0.05% 18,723 All Other RPPC Bottles 0.02% 0.01% 3,032 All Other RPPC Non-Bottles 0.07% 0.08% 12,312

Subtotal 0.92% 0.13% 159,021


Total 100.00% 17,358,359


RESIDENTIAL RPPC DISPOSAL RPPCs accounted for an estimated 1.54% of residential sector waste, representing a substantial increase over the 1995 estimate of 1.05%. Detailed results of the 1999 residential RPPC sampling are found in Table 63.


Table 63: RPPC Composition in Residential Waste

Estimated Percent

+/-

Estimated Tons

#1 PET Soda Bottles 0.15% 0.02% 19,806 #1 PET Custom Bottles 0.32% 0.04% 43,415 #1 PET Non-Bottle Rigids 0.04% 0.01% 4,867 #2 HDPE Natural Bottles 0.40% 0.04% 53,673 #2 HDPE Colored Bottles 0.30% 0.04% 40,326 #2 HDPE Other Containers 0.16% 0.05% 21,975 All Other RPPC Bottles 0.06% 0.01% 8,574 All Other RPPC Non-Bottles 0.11% 0.02% 15,388

Subtotal 1.54% 0.12% 208,022


Total 100.00% 13,525,504


SELF-HAUL RPPC DISPOSAL An estimated 0.21% of self-haul waste was RPPCs. The 1999 estimate is slightly lower than the 1995 estimate of .27%. Detailed self-haul results are presented below in Table 64.

Table 64: RPPC Composition in Self-Haul Waste

Estimated Percent

+/-

Estimated Tons

#1 PET Soda Bottles 0.02% 0.01% 858 #1 PET Custom Bottles 0.02% 0.01% 942 #1 PET Non-Bottle Rigids 0.00% 0.00% 33 #2 HDPE Natural Bottles 0.03% 0.02% 1,297 #2 HDPE Colored Bottles 0.02% 0.01% 1,042 #2 HDPE Other Containers 0.11% 0.07% 5,293 All Other RPPC Bottles 0.01% 0.00% 300 All Other RPPC Non-Bottles 0.00% 0.00% 201

Subtotal 0.21% 0.07% 9,966


Total 100.00% 4,651,591



APPENDIX A: DETAILED METHODOLOGY

A.1 INTRODUCTION

The California Integrated Waste Management Board (CIWMB) commissioned a Statewide Waste Characterization Study in order to obtain data to characterize wastes disposed in the residential, commercial, and self–haul waste streams. These waste streams were characterized through sampling of the waste delivered to disposal sites and waste collected directly from commercial and multifamily generators. The Study provides detailed information on the composition of waste disposed in California during 1999. The design for the Study was prepared by a team of consultants led by the Cascadia Consulting Group, under the direction of CIWMB staff. In addition, an Advisory Group appointed by the CIWMB reviewed and approved the design. This methodology describes the major elements of the Study – ranging from the initial selection of locations where sampling took place, to the sampling procedures, to the approach to analyzing the data. A study like this is challenging because it seeks to apply pure statistical methods within the real-world limitations imposed by budgeting considerations and the day-to-day operations of solid waste transfer and disposal sites. This study sought to find the proper balance – a statistically valid analysis that was cost-effective and a process for gathering data that was not disruptive to facility operators or their customers.

A.2 SELECTION OF REGIONS, DISPOSAL SITES & WASTE SHEDS

The state was divided into regions to ensure that the diversity of geographic, climatic, demographic and economic conditions were appropriately represented in statewide composition estimates. Five geographic regions were delineated to adequately represent this diversity. The analyses that were conducted to define these regions are described below. To obtain a comparable level of data among these regions, five sampling sites were selected randomly from within each region. A total of 25 sites was the maximum number of sites that could be visited under the existing budget and schedule. Data from the single-family residential sector (collected by professional haulers) and the self-haul sector (residential and commercial wastes not collected by professional haulers) were gathered at five disposal sites (landfills or transfer stations) in each region. For single family residential waste and self-hauled waste, an approximately equal number of samples was selected from each region, and weighted averages were used to prepare the statewide waste composition totals. The disposal sites were selected randomly within each region to ensure that the waste samples were representative of the region as a whole and to allow for statistical analysis of the data.

California 1999 Statewide A - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

Each of the 25 sites selected represents a local “waste shed” where waste from different residential and commercial generators is channeled for disposal. Data from the multifamily residential sub-sector and the commercial sector were gathered from samples taken from generator sites within selected waste sheds. For generator sampling, CIWMB staff designated two or three waste sheds in each region, and individual generators were randomly chosen from a list of businesses falling within approximately 20 miles of the selected sites (see Table 71 for a list of waste sheds). Waste sampling occurred during two seasons to account for any seasonal variations in waste disposal patterns. The winter sampling occurred during February, March and April of 1999, and the summer sampling occurred during July, August, and September. Twelve sites were visited during the winter and thirteen during the summer for a total of 25 site visits. The waste was sorted and characterized into the categories included on California’s List of 57 Material Subtypes for Waste Sorting plus eight RPPC categories, as described in Appendix B. These categories were proposed by CIWMB staff and approved by the Advisory Group.

A.2.1 SELECTION OF REGIONS This Study divided California into five regions to account for any demographic and/or geographic variation in waste composition. A random sampling methodology was used to select the sample sites within each region. The stratified sampling plan targeted an equal number of samples for each region, ensuring that the information collected would be comparable statewide and that it would represent the breadth of communities within the state. Three steps were used to select the regions:

1. Identification of areas of the state with similar demographics and geographic features, and tentative assignment of counties to each region.

2. Review of data on all of the counties in the state to confirm the original assignment.

3. Review of the designation by the Advisory Group.


Figure 10: Regions Considered in the Study

M ou n t ain

Cen t ralValley

B ayA reaCoas t al

Sou t h ern

The five regions are shown in Figure 10 and are characterized as follows:

Coastal – includes the counties on the coast that are not in either the Bay Area or Southern regions. The Coastal region is more populated than the rural Mountain region and has a large agricultural component similar to the Central Valley.

Bay Area – includes the counties in the San Francisco Bay Area, which are the more metropolitan counties with a strong industrial component in the economy.

Southern – includes counties that are strongly industrial with large populations and important agricultural influences.

Mountain – includes counties that are primarily rural, with strong agricultural economies, low population density, and a low industrial base.

Central Valley – includes counties between the Sierra Nevada mountains and the Coast Range that have a major agricultural base with important population centers and some manufacturing.


In general, regions were designated so that selected counties were contiguous.6 The counties within each region are listed in Table 65.

Table 65: Counties in the Five Sampling Regions

Coastal Bay Area Southern Mountain Central Valley Del Norte Alameda Imperial Alpine Butte Humboldt Contra Costa Kern Amador Colusa

Mendocino Marin Los Angeles Calaveras Fresno Monterey Napa Orange El Dorado Glenn

San Benito San Francisco Riverside Inyo Kings Santa Cruz San Mateo San Bernardino Lassen Lake

Sonoma Santa Clara San Diego Mariposa Madera Solano San Luis Obispo Modoc Merced Santa Barbara Mono Placer Ventura Nevada Sacramento Plumas San Joaquin Shasta Stanislaus Sierra Sutter Siskiyou Tehama Trinity Tulare Tuolumne Yolo Yuba

ASSIGNMENT OF COUNTIES TO REGIONS Information for distinguishing among regions was drawn from data published in the California Department of Finance’s California County Profiles and from data on population, employment, and taxable sales, which was made available by CIWMB staff. The primary factors used to distinguish among regions were:

• • • •

•

population of each county, population density within each county, level of civilian employment for each county, level of non-agricultural employment for each county (and conversely, level of agricultural employment), average per-capita income for each county.

The profile of each region according to these factors is shown in Table 66. When considered at the level of regions, there are clear differences for each factor.

6 This approach results in designation of at least one county that is not similar to others in the region. Imperial County is in the southeastern end of the state and is primarily agricultural. Due to its geographic location, it was included in the Southern region, but it would have matched characteristics for the Central Valley region. Because Imperial County is not contiguous with the Central Valley region, it was grouped with other counties in the Southern region.


Table 66: Primary Factors for Selection of Sampling Regions

Factor Measurement Coastal Bay Area Southern Mountain Central ValleyAverage 189,871 765,725 1,995,690 42,868 265,365 Low 28,250 120,800 140,500 1,180 18,300 High 426,900 1,653,100 9,488,200 162,700 1,140,600

Average 0.24 4.62 1.15 0.04 0.28Low 0.04 0.25 0.05 0.00 0.02High 0.86 26.03 5.26 0.14 1.85

Average 90,659 380,125 864,320 17,514 110,049 Low 9,230 54,300 40,700 450 7,170 High 220,300 864,300 4,052,600 69,300 513,900

Average 51% 297% 585% 12% 71%Low 10% 80% 30% 5% 5%High 120% 690% 2980% 40% 380%

Average 88% 132% 89% 79% 76%Low 62% 91% 61% 64% 58%High 109% 180% 114% 96% 108%

Counties' average civilian employment

Counties' average persons per acre

Ratio of counties' average non-ag. employment to statewide average non-ag. employment

Ratio of counties' average per-capita income to statewide average per-capita income

Region

Counties' average population, as of 1/1/97

In addition, consideration was given to the set of secondary factors shown in Table 67. These factors also indicate clear differences among the regions.

Table 67: Secondary Factors for Selection of Sampling Regions

Factor Coastal Bay Area Southern Mountain Central ValleyPersons per household 2.7 2.7 3.0 2.4 2.8

Median years of school 13.3 14.2 13.3 13.1 12.9

Unemployment rate 8.8% 4.8% 9.3% 10.0% 12.3%Value of manufacturing, % of state average 44% 400% 548% 31% 57%

Percent of area that is farm land 37.5% 45.9% 26.9% 17.1% 59.4%

Vehicle registrations per capita 0.54 0.61 0.53 0.62 0.5

County tax collections per capita $174 $298 $130 $412 $145

Average Value for Counties in Each Region

The complete data set used is shown in Appendix J. For a county that lies on the border between two neighboring regions, the following process was used to determine the county’s assignment:

1. The county was initially assigned to one of the two neighboring regions, based on the consultants' best judgment.

2. If the county then was responsible for several of its region’s high or low scores for any of the factors (described in Table 66, Table 67, and Appendix J), then the county may have been reassigned to another region if closer inspection of its characteristics indicated that it fit better in another region.

For example, Placer County was originally assigned to the Mountain region. However, Placer County has higher values than any other county in the Mountain region for population and manufacturing employment. Likewise, it has a lower value for percentage of farmland


than any other county in the Mountain region. Placer County was reassigned to the Central Valley region, where its scores are more consistent with those of other counties. ADVISORY GROUP REVIEW At its December 1, 1998 meeting, the Advisory Group reviewed the concept for the Sampling Plan, including the approach used to designate the counties in each region. The Advisory Group concurred in the assignment of counties for each region.

A.2.2 SELECTION OF SITES ESTABLISHING THE UNIVERSE OF POSSIBLE SITES The set of all sites to be considered for inclusion in the Study was derived from two sources. First, CIWMB staff provided a sorted list of transfer stations from the Solid Waste Information System (SWIS) database.7 Second, CIWMB staff provided a list of landfills from a database used to track disposal for the Annual Reports required for AB 939 programs. This landfill database is updated more frequently than the SWIS database. From both the SWIS list and the landfill database, a new list of sites was developed to include only sites that handle more than 100 tons of waste per day. This minimum threshold of waste receipts was established to ensure that there would be enough vehicles from which to select samples. The two databases were merged and sorted by SWIS number, which identifies each site uniquely and also indicates the county in which the site is located. A region number was added to each site entry, and the merged list was sorted by region number. The result was a list of potential sampling sites, including transfer stations, landfills and incinerators, sorted by region. RANDOM SELECTION OF SITES The purpose of the selection process was to randomly select five sites in each region. Each site was required to meet the minimum criteria for use as a sampling site. Each site meeting the criteria had an equal chance of being selected. As the first step in this process, a random number was generated for each potential site, and the sites within each region were sorted according to the order of their random numbers. (This step is called a “random permutation” of the list for each region.) Next, within each region, potential sites were eliminated from the list if they did not meet the minimum criteria required of sampling sites. The minimum criteria were that the site handles waste destined for final disposal (i.e. is not subject to any further processing or sorting), it had a viable way to obtain the weight of the loads brought in by drivers who were interviewed as part of the vehicle survey8, and all three sectors use the facility. Table 68 shows the number of sites in each region that satisfied minimum criteria for selection. Ultimately, all but one site included in the final selection had scales. Also, a few sites were

7 The complete SWIS list encompasses all disposal facilities, including some facilities that are not desired for the Study, such as closed disposal sites, composting sites, tire disposal sites, and others. 8 A strong preference was placed on the ability to weigh every load. If this was not feasible, it was necessary to ensure there was a good method to estimate volumes and convert these volumes to weights. All sites except one had scales; however some sites did not use their scales to weigh small loads. For these loads, a volume to weight conversion was used.


used that processed or sorted materials for recovery, but measures were taken so that samples were either collected or sorted after the selected loads had gone through the process. This way, only materials destined for disposal were characterized.

Table 68: Suitable Sampling Sites in Each Region

Region Number of Sites Coastal 17 Bay Area 35 Southern 107 Mountain 6 Central Valley 48

The sites meeting the minimum criteria were ordered according to their random number, and the five sites from each region that occurred earliest in the list were selected as candidates for disposal site sampling. The initial candidates were contacted as described in the next section. In cases where a site was found to be unsuitable or unavailable, the next was chosen from the randomized list of acceptable sites, again in the order of the random number assigned. In the Bay Area region, the process of selecting the sites was repeated due to concern that too many of the originally randomly selected sites were located in Alameda County. (All five randomly selected sites were in Alameda County.) A new random list of sites was prepared, and a new set of sites was selected. CONTACTING THE SITES The top five sites in each region were contacted to determine their suitability and their willingness to participate in the Study. The list of questions asked of the operator at each site is presented in Appendix K. The sites that were selected for sampling are listed in Table 69.


Table 69: Selected Sampling Sites

SWIS Number TPD* Type

Coastal Region

Monterey Regional Waste Management District/Marina Landfill 27-AA-0010 688 Landfill John Smith Road Class III Landfill 35-AA-0001 244 Landfill Buena Vista Drive Sanitary Landfill 44-AA-0004 421 Landfill Central Landfill 49-AA-0001 1,410 Landfill Johnson Canyon Landfill 27-AA-0005 122 Landfill

Bay Area Region Portrero Hills Landfill 48-AA-0075 618 Landfill South Bayside Transfer Station 41-AA-0016 3,000 Trans. Stn. Davis St. Transfer Station/Resource Recovery Complex 01-AA-0007 624 Trans. Stn. Ox Mountain Landfill 41-AA-0002 2,623 Landfill Berkeley Solid Waste Transfer Station 01-AC-0029 560 Trans. Stn.

Southern Region Universal Refuse Removal Recycling & Transfer Station 37-AA-0929 219 Trans. Stn. Victorville Refuse Disposal Site 36-AA-0045 552 Landfill Falcon Refuse Center 19-AR-0302 3,500 Trans. Stn. Bradley Landfill West and West Extension 19-AR-0008 5,578 Landfill Sunset Environmental Trans. Stn. & Resource Recovery Facility 30-AB-0336 1,700 Trans. Stn.

Mountain Region West Central Landfill 45-AA-0043 357 Landfill South Tahoe Refuse 09-AA-0002 370 Trans. Stn. Western Amador Recycling Facility 03-AA-0008 152 Trans. Stn. City Of Redding Transfer Station/MRF 45-AA-0059 400 Trans. Stn. McCourtney Road Large Volume Transfer Station 29-AA-0010 180 Trans. Stn. Central Valley Region Billy Wright Disposal Site 24-AA-0002 123 Landfill American Avenue Disposal Site 10-AA-0009 1,834 Landfill Fairmead Solid Waste Disposal Site 20-AA-0002 266 Landfill Yolo County Central Landfill 57-AA-0001 636 Landfill Auburn Placer Disposal Transfer Station 31-AA-0601 244 Trans. Stn.

* Tons per day SCHEDULING THE SITES After confirming the sampling sites, another randomization process was used to determine whether sampling at each site would occur during the winter or summer. First, random numbers were assigned to each of the 25 selected sampling sites, and the list was sorted according to the random numbers. Then, the odd numbered sites (1st, 3rd, 5th, etc.) were assigned to be sampled during the summer, and the even numbered (2nd, 4th, 6th, etc.) sites were assigned to the winter season. Table 70 indicates the numbers and types of sites in each region that were scheduled for sampling during each season.


Table 70: Sorting Site Characteristics

Number Sampled Type of Facility Region Winter Summer Landfill Transfer Station Coastal 2 3 5 0 Bay Area 2 3 3 2 Southern 3 2 2 3 Mountain 3 2 1 4 Central Valley 2 3 4 1 Total 12 13 15 10

Once sites were assigned to seasons, one site in each region in each season was designated for generator sampling. In the Southern and Bay Area regions, an extra site was chosen where generator sampling would occur in both seasons, in order to expand the sampling areas in these larger regions. Table 71 shows the selected disposal sites and their scheduled sampling periods, along with the city and county in which each site is located and an indication of whether each site was selected to be a generator sampling site.


Table 71: Sorting Sites, Seasons, and Locations

DisposalSite

SamplingSeason

Facility Type

Generator Waste Shed

City County

Coastal Region Monterey Regional Waste Mgmt. District/Marina Landfill Winter Landfill Marina Monterey John Smith Road Class III Landfill Summer Landfill Hollister San Benito Buena Vista Drive Sanitary Landfill Summer Landfill Watsonville Santa Cruz Central Landfill Winter Landfill Yes Petaluma Sonoma Johnson Canyon Landfill Summer Landfill Yes Gonzales Monterey

Bay Area Region Potrero Hills Landfill Summer Landfill Suisun City Solano South Bayside Transfer Station Winter Trans. Stn. Yes San Carlos San Mateo Davis St. Transfer Station/Resource Recovery Complex Summer Trans. Stn. Yes San Leandro Alameda Kirby Canyon Landfill N/A* Landfill Yes (both seasons) Ellroy Santa Clara Ox Mountain Landfill Winter Landfill Half Moon Bay San Mateo Berkeley Solid Waste Transfer Station Summer Trans. Stn. Berkeley Alameda

Southern Region Universal Refuse Removal Recycling & Transfer Station Summer Trans. Stn. El Cajon San Diego Victorville Refuse Disposal Site Winter Landfill Yes Victorville San Bernardino Falcon Refuse Center Summer Trans. Stn. Los Angeles Los Angeles Bradley Landfill West and West Extension Winter Landfill Yes (both seasons) Los Angeles Los Angeles Southeast Resource Recovery Facility N/A* Incinerator Yes Long Beach Los Angeles Sunset Environmental Trans. Stn. & Resource Recovery Fac. Winter Trans. Stn. Torrence Los Angeles

Mountain Region West Central Landfill Winter Landfill Redding Shasta South Tahoe Refuse Summer Trans. Stn. Yes South Tahoe El Dorado Western Amador Recycling Facility Summer Trans. Stn. Ione Amador City Of Redding Transfer Station/MRF Winter Trans. Stn. Yes Redding Shasta McCourtney Road Large Volume Transfer Station Winter Trans. Stn. Nevada City Nevada

Central Valley Region Billy Wright Disposal Site Summer Landfill Yes Los Banos Merced American Avenue Disposal Site Summer Landfill Tranquility Fresno Fairmead Solid Waste Disposal Site Winter Landfill Chowchilla Madera Yolo County Central Landfill Summer Landfill Davis Yolo Auburn Placer Disposal Transfer Station Winter Trans. Stn. Yes Auburn Placer

* These facilities were originally selected for both disposal site and generator sampling, but it was later determined that they would not be suitable for disposal site sampling due to logistical or other reasons. The original generator sampling areas associated with these facilities were used.

A site coordinator was assigned to each site. The site coordinator (including individuals from CIWMB, Cascadia, Sheri Eiker-Wiles Associates, and Pacific Waste Consulting Group) contacted the site to confirm that the site met the criteria for the study, was agreeable to participating in the study, and to make arrangements for the logistics of the waste sampling. The information collected from the sites included hours of operation, typical vehicle counts, tonnages by sector, nature of operations, and any recycling or processing on site. A summary sheet was prepared for each site. (A sample of the questionnaire is included in Appendix K.) The exact day on which a specific site was sampled was based on a number of factors: site preferences, types of loads received on given days of the week, and efficiencies for the sorting crew. The owner of Sky Valley Associates, the sorting crew used for this study,


proposed a schedule based on parameters stated in the site summary. This proposed schedule was reviewed by the site coordinators and the project manager. Any needed adjustments to the schedule were made, and then the site coordinator contacted the site to confirm the date of the sampling and to finalize the arrangements.

A.2.3 COMMUNICATIONS PLAN Communication with the site operators is one of the key elements of a successful sampling program. After the selection of sampling sites was finalized and approved, the following information was provided to site operators:

• a letter confirming the topics discussed during the interview at which the site operator agreed to participate

• a letter advising the site operator of when the sampling would occur and whether the site would used for sorting generator samples

• a fax or e-mail to the site operator one week before the sampling, reminding of the arrival date and support that would be needed on the day(s) of the sampling event

• a reminder phone call one day before the sampling event Haulers serving the areas that had been designated for generator sampling were notified of the study and informed that the sampling crew would be collecting waste samples from some of their customers.

A.3 DISCUSSION OF NUMBERS OF SAMPLES

The study targeted 1,200 commercial generator samples, which corresponded to an allocation of approximately 40 to 50 samples per industry group. (See section A.4 for a detailed discussion of the allocation of samples among industry groups.) Slightly more than 1,200 commercial samples were collected, and the allocation of actual commercial samples (see Table 74 and Table 75) is in close correspondence with the planned allocation (see Table 73). Differences between the planned and actual number of commercial samples in a specific industry group typically were due to waste that was inaccessible or to scheduling conflicts in obtaining samples. For a few businesses, the industry group designation was changed after the sample had been obtained, based on additional information the consultants learned about the business. A total of 1,207 samples were actually obtained, as reflected in Table 72. A total of 150 samples of single-family residential waste was targeted — 30 in each of the five regions. This is consistent with the California Uniform Waste Disposal Characterization Method. The 30 samples targeted in each region were distributed equally among five different sites in the region. Thus, six samples were targeted at each of 25 different sites throughout the state. A total of 148 samples were obtained, as shown in Table 72. A total of 250 samples of self-haul waste was targeted, with two-thirds of the samples taken from commercial self-haul waste and the remaining one-third from residential self-haul


waste.9 Samples were collected at five sites in each region for a total of 25 sites. Approximately ten samples were taken at each site. As shown in Table 72, a total of 247 self-haul samples was achieved. In some instances, too few residential or self-haul samples were obtained at specific disposal sites. This was usually the result of too few vehicles coming to the site on the day of sampling. On one occasion, enough vehicles arrived, but one of the residential packer trucks subsequently malfunctioned, making the waste inaccessible. Whenever possible, the sampling crew obtained additional samples at subsequent sites to make up for losses along the way. A total of 80 multifamily samples was targeted and obtained, as shown in Table 72. The study design planned to divide the samples among regions based on the numbers of multifamily residences in each region. However this design was somewhat modified. The strict allocation method would have allocated 53 samples to Southern California, and only 1 or 2 samples to the Mountain and Coastal Regions. Instead, slightly more than half of the samples (44 samples) were allocated to the Southern region of the state. Forty samples is the minimum number of samples required by the California Uniform Waste Disposal Characterization Method to characterize the waste disposed by a multifamily-residence population. The remainder of the samples were divided among the other four regions based on the number of multifamily residences in each region. However, each generator waste shed was assigned a minimum of one sample to provide adequate geographic distribution. This required a small adjustment to the allocation. Table 72 summarizes the numbers of samples obtained in each sector and subsector. Additionally, Appendix G presents the waste shed or disposal site location of all samples obtained in each sector and subsector.

Table 72: Numbers of Samples Collected from Each Sector

Sector Number of Samples Targeted

Number of Samples Collected

Commercial 1,200 1,207 Residential 230 228 Single-Family Residential 150 148 Multifamily Residential 80 80

Self-Haul 250 247 Commercial Self-Haul 167 162 Residential Self-Haul 83 85

Total 1,680 1,682

9 For purposes of this study, commercial self-haul loads were those hauled by a commercial enterprise (e.g. contractor, landscaper, etc.) even if the source of the waste was a residential dwelling. Residential self-haul loads were those loads transported by a resident from their home to the disposal site. You had this in a previous version but I didn’t find it anywhere in this version.


A.4 GENERATOR SELECTION AND CAPTURE PROCEDURES

A.4.1 COMMERCIAL GENERATOR SAMPLES The objectives of this task were 1) to estimate the composition of commercially collected waste that is disposed by commercial, industrial, and institutional generators in California and 2) to develop composition profiles for 26 types of generators, or industry groups. ALLOCATION OF COMMERCIAL GENERATOR SAMPLES The study called for a total of 1200 commercial generator samples. The first step in allocating these samples was to select the waste sheds where commercial waste samples would be collected. From the list of randomly selected disposal sites in each region (see Table 69), CIWMB staff randomly selected two to three disposal sites in each region, for a total of twelve sites throughout the state. Using Geographic Information System (GIS) mapping, CIWMB staff selected zip code areas as the boundaries around these disposal sites that roughly corresponded to a 20 mile radius around the site. Businesses located within these “waste sheds” were eligible for generator sampling. Industry groups were designated based on the CIWMB’s standard industry groupings by Standard Industrial Classification (SIC) code (see Appendix E). Then the CIWMB allocated the number of samples to be collected from each industry group during each season according to the following process. First, the number of samples to be collected throughout the state in each industry group were determined. Employment data for 1998 and previously determined business disposal rates (tons disposed per employee per year) were used to estimate total statewide disposal for each industry group, and the groups were ranked by disposal tonnage. A minimum of 40 samples was desired in each of the top 25 groups (groups A through Y in Table 73), each of which contribute at least 1% to the state’s waste stream and in total account for an estimated 95% of the statewide waste disposed. To improve data for the industry groups that contribute the most waste, the minimum number of samples was increased to 50 for each of the top 10 groups. The remaining 13 groups, which together account for less than 5% of the waste, were lumped together and 60 samples (5% of the total number of samples) were assigned to this group as a whole. Employment for each industry group in each region was used to distribute samples among the regions. For example, the Bay Area region accounts for 26% of statewide employment in Group A, therefore 26% of the samples for this group were allocated to that region. In the less populated regions, some of the groups account for much less than 1% of employment and would need less than one sample. However, to ensure that all of the top groups were represented in all regions, samples were assigned so that each region had at least 2 samples (one per season) in each of the top 25 industry groups. The sixty samples assigned to the lumped group were distributed so that these smaller industry groups were sampled in regions where they had significant employment. Once the number of samples in each group in each region was determined, half the samples were assigned to each season. Where odd numbers of samples were assigned, the season to receive the extra sample was chosen randomly. For the lumped group, all seasonal assignments were done randomly. Table 73 shows the overall sampling plan, and Table 74 and Table 75 show the distribution of actual samples collected by season.


Table 73: Targeted Distribution of Commercial Samples, Based on

Regional Employment

Group

Description of Businesses

Minimum No. of

Samples

Coastal

Bay Area

Southern

Mountain

Central

Total

TargetedA Finance / Insurance / Real Estate / Legal 50 2 13 29 2 5 51 B Retail Trade-Restaurants 50 2 11 30 2 6 51 C Retail Trade-Other 50 2 14 28 2 5 51 D Services-Other Misc. 50 2 11 29 2 6 50 E Wholesale Trade-Nondurable Goods 50 4 8 29 2 10 53 F Retail Trade-Auto. Dealers & Service Stns. 50 2 9 31 2 7 51 G Services-Other Professional 50 2 13 28 2 6 51 H Retail Trade-Food Store 50 3 10 29 2 7 51 I Construction 50 2 12 27 2 7 50 J Services-Medical / Health 50 2 11 28 2 8 51 K Manufacturing-Printing / Publishing 40 2 10 25 2 3 42 L Services-Business Services 40 2 12 23 2 4 43 M Services-Education 40 2 8 23 2 7 42 N Public Administration 40 2 8 23 2 6 41 O Services-Hotels / Lodging 40 2 9 23 3 3 40 P Trucking and Warehousing 40 2 8 22 2 8 42 Q Wholesale Trade-Durable Goods 40 2 10 25 2 4 43 R Manufacturing-Other 40 2 6 30 2 4 44 S Transportation-Other 40 2 10 24 2 4 42 T Manufacturing-Electronic Equipment 40 2 17 20 2 2 43 U Manufacturing-Food / Kindred 40 3 6 14 2 16 41 V Manufacturing-Lumber and Wood Products 40 7 3 14 5 11 40 W Manufacturing-Transportation Equipment 40 2 6 32 2 2 44 X Retail Trade-Building Material and Garden 40 2 8 21 2 7 40 Y Manufacturing-Industrial Machinery 40 2 16 20 2 3 43 Z Agriculture / Fisheries 60 * 1 1 1 1 1 5

AA Manufacturing-Instruments / Related 1 1 1 1 1 5 AB Communications 1 1 1 1 1 5 AC Manufacturing-Primary / Fabric. Metal 1 1 1 0 1 4 AD Manufacturing-Apparel / Textile 0 1 1 0 1 3 AE Manufacturing-Furniture / Fixtures 0 1 1 0 1 3 AF Services-Motion Pictures 1 1 1 0 1 4 AG Manufacturing-Chemical / Allied 0 1 1 0 1 3 AH Retail Trade-General Merch. Stores 1 1 1 1 1 5 AI Mining 1 1 1 1 1 5 AJ Transportation-Air 0 1 1 0 1 3 AK Utilities 1 1 1 1 1 5 AL Manufacturing-Paper / Allied 1 1 1 1 1 5 AM Forestry 1 1 1 1 1 5

TOTALS 69 263 641 62 165 1200

* For groups Z through AM, a total of 60 samples was planned. Composition estimates were calculated for the aggregated groups Z through AM. Together, these groups are believed to generate less than 5% of the commercial waste disposed in California.

Within each industry group in each waste shed, samples were distributed so that the majority of the samples were drawn from businesses who contribute large amounts of waste. This was accomplished using the 80/20 rule as a guide. This rule states that generally, 80% of the waste disposed by a group came from the largest businesses which make up about 20% of the group, and 20% of the waste came from the remaining 80% of the (smaller) businesses. The procedure is described in detail below.


RANDOM SELECTION OF BUSINESS SITES Specific businesses were selected randomly using NameFinders, a research organization that uses Dun and Bradstreet business data. For a region containing only one waste shed where generator sampling occurs, the process was as follows:

1. The business sites belonging to each industry grouping were segregated according to the range of numbers of employees at each site. A cut-off point was determined, going from larger business sites to smaller ones, such that business sites above the cut-off point represent approximately 80% of the total employment for all business sites of the industry grouping within the waste shed. The set of business sites that have more employees on site and that represent approximately 80% of the total employment was designated as “Tier 1” businesses. The set of smaller businesses was designated as “Tier 2.”

2. Eighty percent of the required number of business sites for the SIC grouping were drawn randomly from the Tier 1 set, and 20% were drawn randomly from the Tier 2 set.10

3. Specific information about each business site was placed in a database and forwarded to SEWA and CIWMB staff, who contacted the businesses and determined if the business site met the criteria for sampling.

For a region containing two sampled waste sheds, NameFinders calculated the ratio of employment in each industry group that fell within one waste shed verses the employment that fell within the other waste shed. The ratio was used to determine how many business sites of each SIC grouping were required from each waste shed. For example, if the waste shed surrounding the Bradley landfill contained x employees in the “Retail Trade – Other” category, and the region surrounding the Victorville landfill contained

y employees in the same category, then yx

x+

percent of the required businesses was

targeted from the Bradley waste shed, and yx

y+

percent was targeted from the Victorville

waste shed. For each waste shed, the above numbered steps 1 through 3 were followed. Since 1,200 business sites were required for the Study, Cascadia obtained information for approximately 10,000 candidate business sites chosen randomly as described above. Extra business names were obtained to account for ones on the list from NameFinders which were no longer in existence, had recently moved, that could not be reached by phone, or were eliminated through the screening process described below. Each candidate site received a letter from the CIWMB explaining that they had been selected for generator sampling.

10 In order to ensure that there was a large enough pool of candidate business sites to draw from, information on approximately 10,000 businesses was obtained NameFinders, using Dun and Bradstreet data on individual businesses. Specific arrangements were made with approximately 2,700 businesses, or 2.25 times the number of required sites indicated in Table 73.



FINAL SCREENING OF BUSINESS SITES CIWMB staff and SEWA divided the list of candidate sites and contacted the sites to determine:

the number and size of dumpsters at the site,

the frequency of pick-up,

the type of service,

the physical address, and

the procedure for accessing the dumpsters. These contacts proceeded until the required number of participating business sites were secured for each SIC grouping in each waste shed. During the contact process, a business site was screened out of the study if it met any of the following conditions:

It shared dumpster space with other businesses belonging to different SIC groupings or with any residences.

It shared dumpster space with other businesses belonging to the same SIC grouping and it was impossible to obtain an estimate of the volume of waste generated in a given time frame by the selected business.

Its dumpsters were not accessible to the sampling crew.

It refused to permit sampling of its waste.

SEWA or CIWMB staff were unable to obtain the required information on dumpster size, location, time and frequency of pick-up, or dumpster access procedures. However, this information was generally available from waste haulers.

If a business site was screened out, the next randomly selected business in that category was contacted, until the proper number of generators was identified for each industry group.

Table 74: Commercial Samples Collected by Region, Winter Season

Number of Businesses Sampled in Each Region Group Description of Businesses 2-Digit SIC Codes Included Coastal Bay Area Southern Mountain Central Totals

A Finance / Insurance / Real Estate / Legal 60, 61, 62, 63, 64, 65, 67, 81 1 5 9 1 16 B Retail Trade - Restaurants 58 1 4 16 1 4 26 C Retail Trade - Other 56, 57, 59 1 7 13 1 1 23 D Service - Other Misc. 72, 75, 76, 79, 83, 84 1 3 16 1 4 25 E Wholesale Trade - Nondurable Goods 51 2 3 13 1 4 23 F Retail Trade - Automotive Dealers & Service Stations 55 1 5 17 1 3 27 G Services - Other Professional 86, 87, 89 6 15 1 22 H Retail Trade - Food Stores 54 2 4 14 3 23 I Construction 15, 16, 17 1 4 12 1 18 J Services - Medical / Health 80 1 4 12 1 2 20 K Manufacturing - Printing / Publishing 27 1 5 13 1 1 21 L Services - Business Services 73 1 5 11 17 M Services - Education 82 1 3 10 1 1 16 N Public Administration 43, 91, 92, 93, 94, 95, 96, 97 3 4 11 1 3 22 O Services - Hotels / Lodging 70 1 8 11 2 2 24 P Trucking and Warehousing 42 1 6 11 1 2 21 Q Wholesale Trade - Durable Goods 50 1 5 9 1 2 18 R Manufacturing - Other 21, 29, 30, 31, 32, 39 1 3 16 1 1 22 S Transportation - Other 40, 41, 44, 46, 47 1 6 5 1 1 14 T Manufacturing - Electronic Equipment 36 1 7 10 1 19 U Manufacturing - Food / Kindred 20 2 5 4 1 3 15 V Manufacturing - Lumber and Wood Products 24 3 1 6 2 4 16 W Manufacturing - Transportation Equipment 37 1 4 15 1 21 X Retail Trade - Building Material and Garden 52 1 4 10 1 4 20 Y Manufacturing - Industrial Machinery 35 1 7 7 3 18 Z Agriculture / Fisheries 01, 02, 07, 09 1 1 1 3

AA Manufacturing - Instruments / Related 38 1 1 1 3 AB Communications 48 1 1 2 AC Manufacturing - Primary / Fabricated Metal 33, 34 1 1 AD Manufacturing - Apparel / Textiles 22, 23 1 1 AE Manufacturing - Furniture / Fixtures 25 1 1 AF Services - Motion Pictures 78 0 AG Manufacturing - Chemical / Allied 28 1 1 AH Retail Trade - General Merchandise Stores 53 1 1 2 4 AI Mining 10, 12, 13, 14 1 1 1 3 AJ Transportation - Air 45 2 2 AK Utilities 49 1 1 2 AL Manufacturing - Paper / Allied 26 1 1 AM Forestry 08 1 1

Totals 37 124 290 22 59 532


nia 1999 Statewide A - 18 Cascadia Consulting Group, Inc., for tsition Study California Integrated Waste Management Bo

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Table 75: Commercial Samples Collected by Region, Summer Season Number of Businesses Sampled in Each Region Group Description of Businesses 2-Digit SIC Codes Included Coastal Bay Area Southern Mountain Central Totals

A Finance / Insurance / Real Estate / Legal 60, 61, 62, 63, 64, 65, 67, 81 1 6 18 2 5 32 B Retail Trade - Restaurants 58 1 7 14 1 2 25 C Retail Trade - Other 56, 57, 59 1 7 15 1 4 28 D Service - Other Misc. 72, 75, 76, 79, 83, 84 1 8 13 1 2 25 E Wholesale Trade - Nondurable Goods 51 3 5 15 3 4 30 F Retail Trade - Automotive Dealers & Service Stations 55 1 4 14 3 4 26 G Services - Other Professional 86, 87, 89 3 5 12 2 5 27 H Retail Trade - Food Stores 54 1 5 16 2 5 29 I Construction 15, 16, 17 2 5 12 2 6 27 J Services - Medical / Health 80 1 6 15 1 7 30 K Manufacturing - Printing / Publishing 27 2 5

CaliforWaste Compo

13 2 3 25 L Services - Business Services 73 7 13 2 4 26 M Services - Education 82 1 4 14 1 6 26 N Public Administration 43, 91, 92, 93, 94, 95, 96, 97 1 4 12 1 3 21 O Services - Hotels / Lodging 70 1 1 12 1 2 17 P Trucking and Warehousing 42 1 11 2 7 21 Q Wholesale Trade - Durable Goods 50 1 4 16 1 2 24 R Manufacturing - Other 21, 29, 30, 31, 32, 39 1 2 15 1 4 23 S Transportation - Other 40, 41, 44, 46, 47 2 5 16 1 3 27 T Manufacturing - Electronic Equipment 36 2 12 9 2 25 U Manufacturing - Food / Kindred 20 1 2 10 1 12 26 V Manufacturing - Lumber and Wood Products 24 3 4 9 1 7 24 W Manufacturing - Transportation Equipment 37 2 3 17 3 25 X Retail Trade - Building Material and Garden 52 1 5 11 1 3 21 Y Manufacturing - Industrial Machinery 35 2 13 13 2 30 Z Agriculture / Fisheries 01, 02, 07, 09 1 1 2

AA Manufacturing - Instruments / Related 38 3 3 AB Communications 48 2 1 3 AC Manufacturing - Primary / Fabricated Metal 33, 34 1 1 1 3 AD Manufacturing - Apparel / Textiles 22, 23 1 1 2 AE Manufacturing - Furniture / Fixtures 25 1 1 2 AF Services - Motion Pictures 78 1 2 3 AG Manufacturing - Chemical / Allied 28 1 1 1 3 AH Retail Trade - General Merchandise Stores 53 1 1 2 AI Mining 10, 12, 13, 14 1 1 AJ Transportation - Air 45 1 1 2 AK Utilities 49 1 1 1 3 AL Manufacturing - Paper / Allied 26 3 1 4 AM Forestry 08 1 1 2

Totals 36 145 343 36 115 675

Contingency business sites were also obtained for use in sampling in case the Sky Valley Associates (SVA) crew was unable to access the dumpsters of a normal candidate business site in the field. Since it was impossible to determine ahead of time whether a contingency business site would stand in for a Tier 1 or Tier 2 business, contingency business sites were drawn from the Tier 1 set. SEWA and CIWMB staff provided the final list of business sites to SVA along with maps showing how to get to each business site. SVA had copies of the letters that were sent to each business to show to any employee who questioned their activities. If the business denied permission to enter the property, or if the dumpsters were locked or inaccessible, SVA proceeded to the next site without a sample. SVA attempted to replace any missed samples with a sample from a contingency business site. OBTAINING COMMERCIAL GENERATOR SAMPLES Samples were removed from dumpsters so that a vertical cross section “slice” was taken that included waste from the top to the bottom of the bin. The minimum sample size targeted was, in order of priority, either 125 pounds, 1.5 cubic yards, or all of the waste in the bin if less than either of these amounts was present. If there were multiple bins at a site, SVA pulled a sub-sample from each bin. A limited number of very large businesses were selected that had diverse waste streams generated at the sampling site. CIWMB staff determined, with the help of the site contact, what the main waste streams were and the best way to obtain one or more representative samples. Dumpsters were sampled so that each significant waste stream was represented by a sample, and an estimate of the amount of each sampled waste stream was made. Data from these “multi-bin” samples was combined to get the overall composition for the business site. SVA confirmed the number and size of waste containers at the business site. SVA also estimated the volume of waste in each container. As SVA pulled each sample from the containers, they attempted to maintain the relative density of the material as the sample was captured (e.g. they would not place heavy waste from the bottom of the container on the top of a sample). The sample volume was then measured (width, height and length). The collected waste was segregated, labeled, and transported to the disposal site where waste sorting operations were occurring. This waste was sorted by hand into 57 waste categories and then sorted again into 8 RPPC categories. The component weights were entered into a computerized database or recorded on field sheets for later entry. Following the completion of each season of commercial generator sampling, subcontractor Veterans Assistance Network (VAN) contacted each of the sampled business sites to verify its SIC classification, and the number of employees working at the site.

A.4.2 MULTIFAMILY RESIDENTIAL SAMPLES The objective of this task was to estimate the composition of commercially collected waste that is disposed by multifamily residential generators (apartment complexes) in California. ALLOCATION OF MULTIFAMILY RESIDENTIAL SAMPLES Samples of multifamily waste were gathered at randomly selected multifamily complexes in the state. A total of 80 multifamily samples were targeted. The California Uniform Waste Disposal Characterization Method calls for a minimum of 40 samples. In this study, slightly


more than half of the multifamily samples (44 samples) were drawn from the Southern California region, where over fifty percent of the state’s multifamily population resides. The other 36 were split among the remaining four regions based on the number of multifamily units in each region, with a minimum of two samples taken from each region (at least one per waste shed). The waste sheds used for multifamily sampling coincided with the waste sheds used for commercial generator sampling. RANDOM SELECTION OF MULTIFAMILY SITES Sheri Eiker-Wiles Associates (SEWA) randomly selected specific multifamily complexes. One complete list of apartments was assembled for each waste shed. The samples from the Bradley and Southeast Resource Recovery Facility waste sheds in Los Angeles County were compiled from the complete multi-family unit list from the County of Los Angeles. From that source, only those multi-family units with five or more dwellings and which matched the zip codes established for each waste shed were included in the random sort. The lists from the other sampling areas from around the state were amassed through the GTE yellow page listings under “apartments.” Condominiums were not excluded from the lists, but the study kept no record of which complexes were condominiums and which were apartment buildings. Once each list was compiled, SEWA randomly sorted them and began calling to gather the basic information. When the call was made to the owner or the manager, the number of units was confirmed, and only those with five or more units were included in the sampling. The information obtained included the number and size of dumpsters at the site and the frequency of pick-up, as well as specific instructions for accessing the dumpsters. If the property manager or owner could not provide this information, SEWA tried to gather it from waste haulers. Multifamily complexes whose waste was not accessible (e.g., in a locked area) were removed from the list. Multifamily complexes with fewer than five apartment units also were removed from the list. If a complex was removed, the next randomly selected complex in that category was selected. If requested, SEWA would send complexes a formal letter from the CIWMB explaining the study, what was requested of the complex, and that a contractor would visit their site to gather a sample of their waste. If a complex refused permission when contacted, the next randomly selected complex in that category was contacted. Based on the results of this work, SEWA prepared a list of 80 eligible multifamily units, plus a twenty-five percent contingency in each region. The contingency sites were only used if the field crew found that a complex on the selected list had bins that were locked or otherwise inaccessible, or if access was refused at the site. The final list of complexes, along with a map indicating the exact location and directions, was provided to Sky Valley Associates (SVA), the field crew responsible for waste sampling. A follow-up survey by Veterans Assistance Network (VAN) confirmed the number of units in the complex and the average vacancy rate. OBTAINING MULTIFAMILY RESIDENTIAL SAMPLES SVA visited the complexes on the list provided by SEWA and randomly collected a “slice” of waste from a bin or dumpster. Samples contained a vertical cross section of waste from the top to the bottom of the bin. SVA took either a 125 pound sample, a sample volume of 1.5 cubic yards, or all the waste that was at the site, if less than either of these amounts was present. This is consistent with the California Uniform Waste Disposal Characterization


Method. However, because many complexes had less waste than the desired weight or volume minimums on the day of sampling, SEWA and SVA worked to gather additional samples at the end of study to supplement the data. SVA had copies of the letters sent to each complex to show anyone who questioned their activities. If the complex denied permission to enter the property, or if the dumpsters were locked or inaccessible, SVA proceeded to the next site without a sample. SVA attempted to replace any missed samples with a sample from the contingency list. The waste was segregated and labeled, and transported to the disposal site where waste sampling was occurring. The waste was sorted by hand into 57 waste categories and then sorted again into 8 RPPC categories. The weights were entered into a computerized database or on field sheets.

A.4.3 VOLUME AND DENSITY MEASUREMENTS FOR GENERATOR SAMPLES At each generator site that was visited, the collection crew noted the total cubic yardage of bin space that they observed at the site. This number was recorded as the Field Measurement of Dumpster Space, and it was used later in calculations that projected the amount of waste disposed by each generator annually. The volume of dumpsters was recorded in the field using units of cubic yards, based on actual measurements of the dimensions of dumpsters. Field records of compactor space were based on visual estimates. Follow-up phone calls to generators sometimes provided more information about dumpster space. If a more accurate number was later obtained for a generator site, then a Revised Measurement of Dumpster Space was recorded by Cascadia staff and was used in the calculations. For example, a business manager sometimes told us of dumpsters located elsewhere on the property that were not observed by the sampling crew. Similar measurements were recorded for the volume of all trash compactors at each site, and information about compactors was also verified with follow-up phone calls. The actual volume of waste contained in dumpsters on sampling day was measured with a tape measure. Volume was calculated based on the product of dumpster length, dumpster width, and the height of the waste inside the dumpster. The height measurement reflected the distance between the bottom of the inside of the dumpster and the highest point in the mound of waste inside. Later, the ratio of waste volume to dumpster space was converted into a number representing the “fullness” of the dumpsters at each business. (See section A.10 for a description of how the fullness number was used in calculating the annual disposal of waste by each business.)


The density of the waste was calculated based on the ratio between the weight of the sample and the volume of the sample. The sample weight was determined by adding up the weights of all the sorted components of the sample. The sample volume was determined by measuring the dimensions of the sample as it lay on a tarp at the generator site, immediately following extraction of the sample from the dumpster. An attempt was made to maintain the relative density of the sample, as described in section A.4.3 above. For an individual generator site,

volume sample weightsample density sample = .

A.5 DISPOSAL SITE SAMPLE SELECTION

A.5.1 SINGLE-FAMILY RESIDENTIAL WASTE Single-family loads were systematically selected to ensure unbiased and reliable waste composition estimates. Systematic selection consists of taking every nth vehicle after a random start time. To calculate truckload sampling frequency by sector and vehicle type, a sampling interval (n) was established for each. Prior to conducting waste sampling at a disposal site, the site coordinator ascertained the average number of municipal or commercial hauler vehicles delivering residential waste on a given day. This number was divided by the number of samples needed at each site. This determined the sampling interval. For example, if n = 20, the 20th, 40th, etc. truck was selected for sampling. On the day of the sampling, vehicle surveyors assisted the sampling crew by flagging every nth truck and the driver was directed to dump the load in a designated area.

A.5.2 RESIDENTIAL SELF-HAUL AND COMMERCIAL SELF-HAUL WASTE Prior to conducting waste sampling at a disposal site, Cascadia ascertained the average number of self-haulers delivering waste on a given day. Cascadia divided this number by the required 10 samples per site to determine the “every nth” vehicles that were to be selected. Of the 250 samples, one-third were targeted from residential sources and two-thirds from commercial sources. When selecting self-haul vehicles at the disposal site, following the “every nth vehicle” strategy, the first two selected loads were from commercial vehicles, and the next one was from a residential vehicle. Then two more commercial loads were sampled, followed by another residential load, and so forth. If the “nth” self-haul vehicle selected for sampling was of the wrong sub-sector, then the next or “n+1th” self-haul vehicle was selected for sampling. On the day of the sampling, the person conducting vehicle surveys asked every self-haul vehicle if they were disposing residential or commercial waste. Every pre-selected commercial self-haul vehicle and every pre-selected residential self-haul vehicle was flagged. The waste was handled in accordance with the field procedures described in Section A.6.


A.6 SAMPLE SORTING AND DATA RECORDING

A.6.1 WASTE SORTING PROCEDURES This section summarizes the general field procedures that were used at transfer stations and disposal sites. However, the specific protocols and procedures varied among sites so that the waste sampling and vehicle surveying were compatible with the operations of the site, and did not cause undue disruptions. DIVERTING SELECTED VEHICLES When a selected residential or self-haul load was identified at the scalehouse (see sections on Sample Selection for single-family waste and self-haul waste), scalehouse personnel flagged the vehicle with a pair of sample identification sheets. The vehicle was then directed to the sorting area, and the surveyor interviewed the driver to determine the following information:

1) sector: single family residential, residential self-haul, or commercial self-haul

2) for self-haul, the type of activity that generated the waste: residential construction and demolition roofing landscaping commercial/industrial/institutional/other

3) vehicle type EXTRACTING SAMPLES FROM LOADS Sample loads from residential haulers were dumped in an elongated pile. From each sample load, one sorting sample was selected using an imaginary 16-cell grid superimposed over the dumped material. The Field Manager identified the randomly selected cell to be extracted. Then, with the assistance of the landfill’s loader operator, approximately 200 pounds of waste was removed by machine from the designated cell and placed on a tarp. If a loader was not available, samples were removed from the pile by hand. SORTING SAMPLES Once the sample was placed on a tarp, the material was sorted by hand into the prescribed component categories. Plastic laundry baskets were used to contain the separated components. The sorting crew members typically specialize in groups of materials, such as papers or plastics, and sort from the baskets containing their specialty. The Field Manager monitored the homogeneity of the component baskets as they accumulated, rejecting materials that were improperly classified. Open laundry baskets allowed the Field Manager to see the material at all times. The Field Manager also verified the purity of each component as it was weighed, before recording the weight into the database or on field sheets. The materials were sorted to the greatest reasonable level of detail by hand, until no more than a small amount of homogeneous fine material (“mixed residue”) remained. The overall goal was to sort each sample directly into component categories in order to reduce the amount of indistinguishable fines or miscellaneous categories.


Plastics were sorted into 14 categories, which were folded into the six plastic categories required for the waste composition study and the eight plastic categories required for the RPPC study. The translation of the field categories to the waste composition and RPPC categories is diagrammed in Figure 11 below.

Figure 11: Translation of Field Sorting Categories to Study Categories of Plastics

Waste Composition Categories Field Categories RPPC Study Categories

PETE Containers #1 Pop #1 PET Soda Bottles#1 Custom #1 PET Custom Bottles#1 Tub #1 PET Non-Bottle Rigids#1 Non-RPPC

HDPE Containers #2 Natural #2 HDPE Natural Bottles#2 Colored #2 HDPE Colored Bottles#2 Tub #2 HDPE Other Containers#2 Non-RPPC

Miscellaneous Plastic Containers Other Bottles All Other RPPC BottlesOther Tubs All Other RPPC Non-BottlesOther Non-RPPC

Film Plastic FilmDurable Plastic Items DurableRemainder/Composite Plastic R/C Plastic

After the plastics data were gathered, the weights were adjusted for contamination, based on the data from the 1995 decontamination study. (See Appendix I). RECORDING SAMPLE DATA The Field Manager recorded composition weights as well as the information obtained from the driver interview in the field using either a hand-held computer or field sheets. The database and corresponding data-entry forms were developed prior to the start of sampling to ensure accuracy, consistency among forms, and efficient recording of data. To ensure additional accuracy, the electronic data-entry forms included validation rules to prevent out-of-range values. (For example, the database will not allow “pick-up truck” to be entered as the vehicle type for a sample from a commercially hauled load).

A.6.2 HEALTH AND SAFETY PROTECTION The sampling crew has an established, on-going safety and training program. Before sampling began at each site the crew first identified and discussed all of the unique hazards, emergency procedures, and operational restrictions that might be present. The contractor has written safety procedures and conduct guidelines, including a Bloodborne Pathogen Exposure Control Plan. These procedures are updated whenever new safety information, products or regulations appear. In addition to continued training and practice, the sampling crew used its own high-quality safety equipment, field gear, and scales.


A.7 VEHICLE SURVEY

The objective of the vehicle surveys was to estimate the portion of California’s waste contributed by each of the residential, commercial, and self-haul sectors. The surveys provided an estimate of the fraction of the overall waste stream contributed by each of the residential, self-haul, and commercial sectors and subsectors. The vehicle surveys occurred at 24 of the 25 randomly selected sampling sites (See Table 71). The surveys were conducted with the drivers of all vehicles bringing waste to the sites during an eight-hour period.11 A total of 3,648 surveys were completed. Appendix H presents the number of surveys conducted at each disposal site.

A.7.1 SURVEY APPROACH The surveys were conducted at each sampling site on the same day disposal site sampling occurred. The surveyor was generally on site for an eight-hour period. At sites where there was heavy vehicle traffic, two or more surveyors were used. The surveyor conducted a brief interview with the driver of each vehicle entering the site. The surveyor recorded the following data for each vehicle:

information to enable identification of the weight of loads that did not have a tare weight on file at the scalehouse

the weight of the contents as recorded in the scalehouse12

the type of vehicle The data gathered during the interview varied depending on whether the load was self-hauled or delivered by a public or private waste collection organization.

If the vehicle was from a company that collects waste, the driver was asked the following questions:

Is the waste from a single–family dwelling, multi–family dwelling, or commercial source?

If not all from one source, what is the percentage in the load from each?

If the vehicle was driven by a self-haul customer, the following question was asked:

Is the source of waste residential, construction and demolition, roofing, landscaping, or other (i.e., general industrial and commercial)?

A copy of the form that was used to collect the data is included in Appendix D. The surveyors received training in use of the survey form and the survey was tested at a transfer station before the first survey period. 11 In rare cases, it was necessary to skip some vehicles to maintain safe and efficient traffic flows. 12 If the operators of a site typically recorded the volume of a load rather than its actual weight, the volume-to-weight conversion used by the gate attendant at that site was used to convert volume to weight. The weight recorded for the load was the same weight as recorded by the gate attendant.


Data taken on the survey forms was checked for accuracy in the field. The surveyor checked the forms to ensure that all appropriate information had been gathered. The survey supervisor checked the surveys after they were returned to the office to confirm that all the required data was properly entered. Survey entries with errors or that were incomplete were not used. Following each survey period (winter and summer), Veterans Assistance Network entered the vehicle survey data into a Microsoft Access database. Following data entry, Cascadia compared entries with the written field record, and any data entry errors were addressed. Two separate checks occurred. First, at various points during data entry, Cascadia randomly checked more than ten percent of the field records to ensure quality of data entry was sufficient. (The first time this was completed, errors were discovered and VAN was required to re-do the data entry. Subsequent random checks found the data entry to be precise). Second, upon completion of data entry, Cascadia checked every tonnage entry to ensure that the quantity data was accurately entered. During all of these checks, if data entry errors or omissions could not be resolved, the entry was deleted.

A.8 BASE POPULATION AND DISPOSAL DATA

A.8.1 ANNUAL TONNAGE ESTIMATES FOR EACH REGION AND STATEWIDE The projections of statewide waste tonnage by sector and subsector relied on applying the vehicle survey results to the reported total amount of waste disposed in each region of the state in 1998. The tonnage in each sector and subsector was then added from the regional level to produce a figure for the state level. The total amount of waste disposed in each region is shown in Table 76. (See section A.10 for a detailed description of the calculation methods.)

Table 76: Total Waste Disposal (Tons) in Each County and Region, 1998

Coastal Bay Area Southern Mountain Central Del Norte 19,012 Alameda 2,256,929 Imperial 159,419 Alpine 0 Butte 169,280 Humboldt 84,197 Contra Costa 601,562 Kern 666,609 Amador 11,653 Colusa 0 Mendocino 52,053 Marin 312,801 Los Angeles 10,081,953 Calaveras 27,641 Fresno 709,713 Monterey 480,631 Napa 37,710 Orange 4,670,966 El Dorado 255 Glenn 20,894 San Benito 82,624 San Francisco 0 Riverside 1,615,275 Inyo 14,771 Kings 103,518 Santa Cruz 236,363 San Mateo 953,530 San Bernardino 1,278,510 Lassen 14,070 Lake 50,163 Sonoma 455,433 Santa Clara 1,637,992 San Diego 2,653,604 Mariposa 11,519 Madera 85,821 Solano 612,073 San Luis Obispo 229,197 Modoc 0 Merced 208,485 Santa Barbara 438,328 Mono 28,058 Placer 175,086 Ventura 920,992 Nevada 0 Sacramento 1,115,822 Plumas 1,644 San Joaquin 1,126,064 Shasta 173,274 Stanislaus 182,838 Sierra 2,525 Sutter 0 Siskiyou 17,328 Tehama 42,892 Trinity 4,315 Tulare 313,125 Tuolumne 0 Yolo 210,029 Yuba 176,907 Totals: 1,410,313 6,412,597 22,714,853 307,053 4,690,637

Total Statewide: 35,535,453 tons


Source: CIWMB Disposal Reporting System. Counties showing 0 tons disposed do not have local disposal facilities and send waste to other counties.

A.8.2 NUMBER OF APARTMENTS IN EACH REGION AND STATEWIDE Estimates of the composition of multifamily sector waste at the state level relied on information about the number of apartment units in each region. (See section A.10 for a detailed description of the calculation methods.) The numbers of apartment units in each region are presented in Table 77.

Table 77: Numbers of Multifamily Units by County and Region, 1998

Coastal Bay Area Southern Mountain Central Del Norte 519 Alameda 145,549 Imperial 6,296 Alpine 328 Butte 10,508 Humboldt 4,718 Contra Costa 62,200 Kern 23,894 Amador 680 Colusa 473 Mendocino 2,808 Marin 22,021 Los Angeles 1,122,604 Calaveras 552 Fresno 49,402 Monterey 24,286 Napa 5,715 Orange 246,570 El Dorado 5,734 Glenn 790 San Benito 906 San Francisco 150,620 Riverside 79,165 Inyo 464 Kings 3,926 Santa Cruz 12,478 San Mateo 69,278 San Bernardino 82,637 Lassen 761 Lake 1,115 Sonoma 21,945 Santa Clara 141,193 San Diego 297,373 Mariposa 305 Madera 3,033 Solano 19,698 San Luis Obispo 10,880 Modoc 207 Merced 7,178 Santa Barbara 30,196 Mono 3,386 Placer 9,508 Ventura 38,297 Nevada 2,475 Sacramento 97,223 Plumas 597 San Joaquin 28,402 Shasta 5,609 Stanislaus 21,945 Sierra 105 Sutter 4,088 Siskiyou 1,499 Tehama 1,601 Trinity 259 Tulare 8,894 Tuolumne 1,412 Yolo 14,462 Yuba 2,613 Totals: 67,660 616,274 1,937,912 24,373 265,161

Total Statewide: 2,911,380 units

Information was taken from California Department of Finance data on counties, 1998.

A.9 QUALITY CONTROL PROCEDURES

Verification procedures were built into the processes for gathering and recording data during each segment of the study. These processes were discussed with each team member responsible for collecting or entering data, to ensure that data were managed consistently throughout the Study.

A.9.1 IDENTIFICATION OF COMMERCIAL AND MULTI-FAMILY GENERATORS Initially, each set of candidate business sites obtained from NameFinders was screened to ensure that the set was drawn from the correct geographical area and included businesses in the correct SIC groups. Information about the business sites was then placed in a different database for each waste shed and e-mailed to the individual responsible for contacting businesses in that waste shed. As the calls proceeded, more information about each business was entered into the databases.


Following completion of calls, the set of confirmed businesses and multifamily complexes was reviewed by Cascadia staff to ensure that all necessary information had been collected to permit ready access to the waste for sampling and to permit extrapolation of quantities of waste disposed across entire SIC groups. If all the required information was not present for a business, the business record was returned to the caller for completion. If all information was present, the business record was placed in a separate "generator" database built to house information about businesses and multifamily complexes that were actually sampled. A parallel set of data was placed in the generator database for multifamily generators that were participating in the Study. (See Appendix D for a snapshot of the types of information contained in the generator recruitment database.) At regular intervals, summaries of business site and multifamily site records were e-mailed to SVA for inclusion in the generator sampling schedule. Reports from SVA about any sites that were not actually sampled were recorded, and the corresponding site records in the database were marked as having not been sampled. Following the completion of each season of generator sampling, subcontractor VAN contacted the sampled business sites to determine exact employment on site and to verify SIC classification. This information was entered by VAN into the generator database.

A.9.2 VEHICLE SURVEYS Surveys of the drivers of individual vehicles at disposal sites were recorded on separate lines on a survey form (see Appendix D). In addition to vehicle-specific information, the surveyor recorded his/her name, the location, and the date on which each page of the form was completed. Pacific Waste Consulting Group reviewed the vehicle surveys to ensure consistent and correct recording of vehicle information and to incorporate volume-to-weight conversion factors when necessary for sites that did not weigh some vehicles. Following the completion of each season's vehicle surveys, subcontractor VAN entered the information from the survey forms into a database. After the data entry was completed, Cascadia compared entries with the written field record, and any data entry errors were addressed. Two separate checks occurred. First, at various points during data entry, Cascadia randomly checked more than ten percent of the field records to ensure that the quality of data entry was sufficient. (The first time this was completed, errors were discovered and VAN was required to re-do the data entry. Subsequent random checks found the data entry to be precise). Second, upon completion of data entry, Cascadia checked every tonnage entry to ensure that the quantity data was accurately entered. During all of these checks, if data entry errors or omissions could not be resolved, the entry was deleted.

A.9.3 WASTE SAMPLING For generator and disposal samples alike, information on the composition of each sample was entered into the field composition database. During the winter sampling period, subcontractor Sky Valley Associates recorded material weights from each sample on a hand-held computer. Each entry was stated by the person weighing the material and then was restated by the person recording the weights. On occasion, material weights were recorded on paper forms in the field. These records were subsequently entered into the project database, with one person reading the numbers aloud and another person typing them. In such cases, each entry was then verified again after the entire set of sample


records had been completed. Information accumulated by the sampling crew was e-mailed to Cascadia on a regular basis and was transferred to a master composition database. (See Appendix D for a snapshot of the information contained in the field composition database.) During the summer sampling period, subcontractor VAN entered the composition data from paper field records, and each entry was verified by Cascadia staff.

A.10 DESCRIPTION OF STATISTICAL PROCEDURES USED

Data gathered from three sources (vehicle surveys, disposal site sampling, and generator sampling) were combined to yield estimates of percentages and tonnages of materials in California’s waste stream. This section describes the methodology used to obtain each estimate and its associated variability. The general calculation strategy involved two common themes: (1) the use of ratio estimators to determine the composition percentages of the waste stream; and (2) aggregation of sample data from the sampling unit to region and to the statewide level. A ratio estimator involves the ratio of two quantities, both of which are random variables. For most of this study, the basic ratio estimator was derived as the ratio of the weight of material in a given sample over the total weight of the sample. While the aggregation up to the state level varied by sector, the general procedure involved creating a new ratio estimator by weighting across ratios from a lower level. The details for each sector are given in the subsections that follow. Statistical analyses were run under either Windows 98 or Windows NT using programs written in S-PLUS 4.5 Professional.

A.10.1 VEHICLE SURVEYS Vehicle survey data were used to estimate the percentage of state waste disposed by commercial, residential and self-haul sectors. Data from a total of 24 sites across five regions13 were aggregated to obtain individual tonnage estimates for overall commercial, commercial self-haul (including the sectors roofing, landscaping, construction and demolition, and other), residential self-haul, single-family residential, and multi-family residential sectors. ESTIMATING PERCENTAGES The following steps were used to estimate the statewide percentages for each sector.

1. Calculate the sum of the net weights of all vehicles surveyed at a given site, a given region, and a given sector. Repeat this for each site/region/sector combination, resulting in 24 sums per sector.

∑∑ ∑=

i j kR S Secijkijk wN

13 Vehicle surveys were conducted at five sites in each of four regions of the state and at four sites in the Southern region, for a total of 24 sites.


where = region i, for i = 1,...,5; iR

jS = site j, for j = 1,...,5; = sector k, for k = 1,...,8 for each of the eight sectors; and, kSec

= weight of load in region i, site j, sector k. ijkw


2. Calculate the sum of the net weights of all surveyed loads at a given site and a given region. Repeat this for each site/region combination, resulting in 24 sums.

∑∑=

i iR Sijij wD

where = region i, for i = 1,...,5; iR

jS = site j, for j = 1,...,5; and,

ijw = total weight of all loads in region i, site j.

3. Calculate weighted region estimates by sector from the sums in 1 and 2 above.

∑

∑

=

=

×

×= 5

1

5

1

jijij

jijkij

ik

Da

NaRVS

where = annual tons for region i, site j. ija

4. Calculate weighted statewide estimates by sector from region estimates in 3 above.

∑

∑

=

−

×

×= 5

1

5

1

iii

iiki

k

RDa

RNaSVS

where = annual tons for region i (including all sites, sampled or not); ia

, the numerator in step 3 above; and, ∑=

×=5

1jijkijik NaRN

, the denominator in step 3 above. ∑=

×=5

1jijiji DaRD


EXAMPLE CALCULATIONS FOR VEHICLE SURVEY DATA: COMMERCIAL SECTOR

The following example vehicle survey data is for 2 regions, 3 disposal sites

per region.

SampleID SectorID SiteID Tons Region 8 1 12 8.81 1

83 1 12 9.38 1 85 1 14 12.36 1 245 1 14 9.78 1 246 1 15 6.21 1 612 1 15 2.47 1 620 1 15 6.41 1

1039 1 16 3.44 2 1040 1 16 7.76 2 1045 1 16 1.52 2 1597 1 19 9.40 2 1604 1 19 0.10 2 1611 1 19 0.07 2 1390 1 20 7.88 2 1391 1 20 3.30 2 1392 1 20 7.10 2 1399 1 20 1.72 2

Example annual tons data, by disposal sites, within region.

Region SiteID Annual Tons 1 12 458712 1 14 407706 1 15 59622 2 16 51626 2 19 87794 2 20 45256

Example annual tons data by region (including disposal sites not sampled).

Region Annual Tons 1 6412597 2 4690637

1. Calculate the sum of the weights of all samples from a given disposal sites

and a given region. Since there are two regions, with three sites per region, this will yield six separate sums:

1,12 8.81 9.38 18.19N = + = 1,14 12.36 9.78 22.14N = + = 1,15 6.21 2.47 6.41 15.09N = + + =

2,16 3.44 7.76 1.52 12.72N = + + = 2,19 9.40 .10 .07 9.57N = + + =

2,20 7.88 3.30 7.10 18.28N = + + =


2. Calculate the sum of the weights of all surveyed loads from a given site and a

given region. In this case we would need the data for all other sectors. These values represent the total weight of all surveyed loads for the given site and region. For simplicity, assume the following surveyed load weights for each site:

1,12 50.70D = 1,14 56.90D = 1,15 72.40D =

2,16 30.25D = 2,19 47.29D = 2,20 52.35D =

3. Calculate weighted region estimates from the sums in steps 1 and 2 above.

( ) ( ) ( )( ) ( ) ( )1

458712 18.19 407706 22.14 59622 15.09 18,270,278458712 50.70 407706 56.90 59622 72.40 50,771,803

RE× + × + ×

= =× + × + ×

( ) ( ) ( )( ) ( ) ( )2

51626 12.72 87794 9.57 45256 18.28 2,324,20651626 30.25 87794 47.29 45256 52.35 8,082,616

RE× + × + ×

= =× + × + ×

4. Calculate weighted statewide estimates from region estimates in 3 above.

( ) ( )( ) ( )

14

14

6,412,597 18,270,278 4,690,637 2,324,206 1.28 10 0.356,412,597 50,771,803 4,690,637 8,082,616 3.63 10

SC× + × ×

= = =× + × ×

Thus, the statewide commercial sector accounts for 35% of the total waste

stream. EXTRAPOLATING TO TONNAGES Annual tonnages for the various sectors of the vehicle survey were obtained by multiplying the individual sector statewide estimates by the statewide annual tonnage value; i.e.

35,535,453k kTVS SVS= × . The statewide annual tonnage is assumed to be a constant and was based on 1998 figures from California’s Disposal Reporting System.

A.10.2 CALCULATING COMPOSITION PERCENTAGES FROM SAMPLES The calculation of composition percentages involved using data from generator sampling and disposal site sampling, combined with vehicle survey results. The methods varied somewhat by sector. Specific calculations, by sector, are outlined in the following sections. COMMERCIAL WASTE Data obtained from generator sampling were used to estimate the statewide waste stream composition for the commercial sector. Commercial compositions were estimated for 26 industry groups, as well as for the overall commercial sector. INDUSTRY GROUP COMPOSITIONS

The following steps were used to estimate the commercial compositions for each industry group.


1. Aggregate compositions by industry group and region.

=∑∑∑

∑∑i j k

i j

ijkR I M

ijkij

R I

wIC

w

where = region , for iR i = 1,...,5i ; jI = industry group j , for =1,...,26j ;

= material type , for kM k =1,...,57k ; = weight of sample for region i , industry groupijkw j , material type ; and, k

= total weight of all samples in region , industry groupijw i j . 2. Calculate weighted statewide estimates for each material type within each industry

group by aggregating over regions.

=

=

×=

×

∑

∑

5

15

1

ij ijki

jk

ij iki

a NIC

a D

where = employment for region i , industry groupija j ;

=∑∑∑ , the numerator in step 1 above; and, ijkNi j k

ijkR I M

w

= , the denominator in step 1 above. ikD ∑∑i j

ijR I

w

OVERALL STATE COMMERCIAL COMPOSITION

The proportion for each material in the overall statewide commercial waste stream was calculated by aggregating individual industry group compositions.

=

=

×=

×

∑

∑

26

126

1

j jj

k

j kj

a NCOM

a D

k

where ja = statewide employment for industry group j ;

jkN = , the numerator in step 2 above; and, 5

1ij ijk

ia N

=

×∑

= , the denominator in step 2 above. kD5

1ij ik

ia D

=

×∑


EXTRAPOLATING TO TONNAGES

Material tonnages for the overall commercial waste stream were obtained by multiplying the individual material type proportions by the commercial tonnage value resulting from the vehicle survey analysis; i.e. the tonnage for material type in the entire commercial sector was calculated as .

k17,358,359k kTC COM= ×

Material tonnages within each industry group were derived as follows. First, a figure was calculated for the estimated Tons Per Employee Per Year (TPEPY) for each industry group. (See Section A.10.3 for a description of TPEPY.) Second, the TPEPY figure for an industry group was multiplied by the number of employees statewide in that industry group to produce an estimate of the tons of waste disposed by the industry group. The total tons of waste disposed by all industry groups was constrained to equal 17,358,359 tons, which was the figure determined by the vehicle surveys. Finally, the tons of each material disposed by an individual industry group were calculated by multiplying the individual material type proportions by the tonnage for the relevant industry group. RESIDENTIAL WASTE Estimates for the residential sector were derived from a combination of data from generator and disposal site sampling. Data from disposal site sampling were used to estimate the composition for the single-family sector, while data from generator sampling were used to estimate the multi-family sector. SINGLE-FAMILY

The following steps were used to estimate the single-family residential composition.

1. Calculate the sum of the weight of samples across all sites from a given region, for a given material type.

=

= ∑∑∑5

1i k

ik ijkR M j

N w

where = region i , for iR =1,...,5i ;

= material type , for kM k =1,...,57k ; j = sites within region ; and, i

= weight of sample in region , site ijkw i j , material type k . 2. Calculate the sum of the total weights of all samples from a given region.

=

= ∑∑5

1i

i iR j

D w j


j =sites within region ; and, i

ijw = total weight of all samples in region , site i j .


3. Calculate weighted statewide estimates using sums in 1 and 2 above.

5

15

1

i iki

k

i ii

a NSSF

a D

=

=

×=

×

∑

∑

where = estimated annual tons for the single-family sector, region i . This

weight was estimated using regional sector estimates from the vehicle survey results.

ia

4. Extrapolate tonnages. Single-family residential tonnages were obtained by

multiplying the individual material type proportions by the single-family residential tonnage value resulting from the vehicle survey analysis; i.e.

. 739,955,9×= kk SSFTSF MULTI-FAMILY

The following steps were used to estimate the multi-family residential composition:

1. Calculate the sum of the weight of samples from a given region, for a given material type.

= ∑∑

i k

ik ikR M

N w


= material type , for kM k =1,...,57k ; and, = weight of an individual sample in region i , for material type . ikw k

2. Calculate the sum of the total weights of all samples from a given region.

= ∑i

i iR

D w

where = region i , for iR =1,...,5i ; and,

iw = total weight of all samples in region . i 3. Calculate weighted statewide estimates using sums in 1 and 2 above.

5

15

1

i ii

k

i ii

a NSMF

a D

=

=

×=

×

∑

∑

k

where = number of apartments in region i . ia


4. Extrapolate tonnages. Multifamily residential tonnages were obtained by multiplying the individual material type proportions by the multifamily residential tonnage value resulting from the vehicle survey analysis; i.e. 888,569,3×= kk SMFTMF .

OVERALL RESIDENTIAL

The overall statewide residential composition was estimated as weighted average of the single-family and multi-family estimates. The weights were based on the proportions of waste generated by single-family and multi-family sectors, as determined from the vehicle survey analysis; i.e. the overall residential proportion of waste for a given material type was calculated as

k( ) ( ).736 .264k k k . Overall residential tonnages were

obtained by multiplying the individual material type proportions by the residential tonnage value resulting from the vehicle survey analysis; i.e.

RES SSF SMF= × + ×

13,525,504k kTR RES= × . SELF-HAUL WASTE

Data obtained from disposal site sampling were used to estimate the statewide waste stream composition for the self-haul sector. The computations for the commercial and residential subsectors mirror those for the single-family residential subsector described in the previous section. The only difference in the computations was in the weights ia . For self-haul estimates, represents estimated annual tons for the commercial (or residential) subsector, for region i . These weights were estimated using regional sector estimates from the vehicle survey results.

ia

OVERALL SELF-HAUL

The following steps were used to estimate the overall self-haul composition:

1. Calculate the sum of the weight of samples across all sites from a given region, for a given material type, for both the commercial and residential subsectors.

=

= ∑∑∑∑5

1l i k

ikl ijklS R M j

N w

where = subsector l, for l= 1 (commercial) and 2 (residential); lS

iR = region i , for =1,...,5i ; = material type , for kM k =1,...,57k ; j = sites within region ; and, i

= weight of sample in region , siteijklw i j , material type , subsector l. k 2. Calculate the sum of the total weights of all samples from a given region.

=

= ∑∑∑5

1l i

il ijlS R j

D w

where = subsector l, for l= 1 (commercial) and 2 (residential); lS

iR = region i , for =1,...,5i ; j =sites within region ; and, i


ijlw = total weight of all samples in region , site i j , subsector l.

3. Calculate weighted regional self-haul estimates using sums in 1 and 2 above.

( ) ( )( ) ( )

1 1 2 2

1 1 2 2

i ik i ikik

i i i i

a N a NRSH

a D a D× + ×

=× + ×

where and = regional estimated annual tons for the commercial and

residential subsectors, respectively. These weights were estimated using regional sector estimates from the vehicle survey results.

1 ia 2ia

4. Calculate weighted statewide estimates using the regional estimates in 3 above.

5

15

1

i ii

k

i ii

a NSSH

a D

=

=

×=

×

∑

∑

k

where = estimated annual tons for region i , based on vehicle survey results; ia =ikN ( ) ( )× + ×1 1 2 2i ik i ika N a N , the numerator in step 3 above; and,

=iD ( ) ( )× + ×1 1 2 2i i i ia D a D , the denominator in step 3 above.

Overall self-haul tonnages were obtained by multiplying the individual material type proportions by the self-haul tonnage value resulting from the vehicle survey analysis; i.e.

. 4,651,591k kTSH SSH= ×

OVERALL STATEWIDE COMPOSITION The overall statewide waste stream composition was calculated as a weighted average of the average commercial, residential and self-haul estimates. The weights were based on the proportions of waste generated by the commercial, residential and self-haul sectors, as determined from the vehicle survey analysis; i.e. the overall statewide proportion of waste for a given material type was calculated as k

( ) ( ) ( ).488 .381 .131k k kOCOMP COM RES SSH= × + × + × k . Overall statewide tonnages were obtained by multiplying the individual material type proportions by the annual statewide tonnage value; 35,535,453k kTCOMP OCOMP= × .

A.10.3 CALCULATING TONS PER EMPLOYEE PER YEAR (TPEPY) An estimate of tons per employee per year was calculated statewide for the commercial sector by industry groups. The calculations were as follows: 1. Calculate an average sample density for each industry group. Only samples that (a)

weighed more than 50 pounds and that (b) were obtained on the day of or day before trash collection and/or the bin was full, were used in this estimation.


=∑∑

jkj

kjk

j

WDen

V

where k = industry group, =1,...,26k ;

j = site whose number varied by industry group; jkW = weight of sample for industry group k , at site j ; and,

jkV = volume of sample for industry group , at site k j . An overall statewide average density was calculated as a weighted sum of the average densities for each industry group:

26

1k k

kDen a Den

=

= ×∑ where = the proportion of statewide employment for industry group k ; and, ka = the average volume per employee per year for industry group . kDen k

2. Assign a density to each sample. If the sample met the inclusion criteria in step 1, then

the density was the sample density, j jW V ; otherwise, assign the average density, for the appropriate industry group . kDen k

3. Assign a bin fullness to each sample, where bin fullness is defined as observed trash

volume divided by observed dumpster volume. If the sample met the inclusion criteria in step 1 and there was data for observed trash volume and observed dumpster volume, then the observed bin fullness was used as the value for bin fullness. Otherwise, assign the average bin fullness for the appropriate industry group. Average bin fullness was calculated as:

=∑ jk

j jkk

k

TVDV

BFn

where j = site whose number varied by industry group; jkTV = observed trash volume for industry group , at site k j ;

jkDV = observed dumpster volume for industry group , at site k j ; and, = the number of qualified sites in industry group k . kn

4. Estimate tons per site per year (TPSPY) for each commercial site.


( ) ( )( )× × + × × ×=

4

2000j j j j j

j

Den BC BF Den CC APTPSPY

j

where jDen = sample density;

jBC = site bin capacity;

jBF = site bin fullness;

jCC = site compactor capacity;

jAP =annual site pickups.

As with the density and bin fullness calculations in steps 2 and 3, respectively, an average TPSPY for the given industry group was assigned to sites that did not have sufficient data to estimate a site specific TPSPY.

5. Within each region, an average TPEPY was calculated for each of the industry groups. The average TPEPY was calculated as a ratio estimator.

ijkj

ikijk

j

TPSPYTPEPY

Emp=∑∑

where = tons per site per year at siteijkTPSPY j for industry group , within region ;

and, k i

= number of employees at siteijkEmp j for industry group k , within region . i

6. Calculate weighted statewide estimates, by industry group, using the regional estimates in 5 above.

5

15

1

( )

( )

ik ijki j

k

ik ijki j

a TPSPYTPEPY

a Emp

=

=

×=

×

∑ ∑

∑ ∑

where = number of employees in region , for industry group ; ika i k = tons per site per year at siteijkTPSPY j for industry group , within region ;

and, k i

= number of employees at siteijkEmp j for industry group k , within region . i

An overall statewide tons per employee per year was calculated as a weighted sum of the tons for each industry group:

26

1k k

kTPEPY a TPEPY

=

= ×∑


where = the proportion of statewide employment for industry group k ; and, ka = the average volume per employee per year for industry group . kTPEPY k TPEPY estimates were scaled up to produce tonnage estimates consistent with the amount of commercial waste estimated using the vehicle surveys. The TPEPY estimates for each industry group, as calculated above, were multiplied by the number of employees in each industry group to produce a tonnage figure. The tonnage figures were then summed across all industry groups, resulting in a number, 14,593,656, which was less than the 17,358,359 commercial tons that were projected by the vehicle survey analysis. The TPEPY figure for each industry group was then inflated by a factor of 1.189, which is the ratio

17,358,35914,593,656 .

A.10.4 CALCULATING AVERAGE VOLUME PER EMPLOYEE PER YEAR

The average volume per employee per year was calculated for each industry group as follows.

2000kk

k

TPEPYYPEPYDen

×=

where k = tons per employee per year for industry group k , calculated as TPEPY

described in step 6, section A.10.3; 2000 = conversion factor from tons to pounds; and, k = average density for industry group , calculated as described in step 1, Den k section A.10.3. An overall statewide average volume per employee per year was calculated as a weighted sum of the volumes for each industry group:

26

1k k

kYPEPY a YPEPY

=

= ×∑ where = the proportion of statewide employment for industry group k ; and, ka = the average volume per employee per year for industry group . kYPEPY k

A.10.5 VARIANCE CALCULATIONS Due to the complexity of the sampling design and the need to aggregate up over several levels of ratio estimators, several different approaches were used in calculating the standard errors of the various estimates. Bootstrap resampling was most commonly used, although in a few situations, this method was not employed. The particular methods and when they were applied, are described in the following sections. BOOTSTRAP RESAMPLING Bootstrap resampling was the preferred method for standard error calculations, and was used whenever possible. Specifically, bootstrapping was applied to the vehicle survey results, the waste stream composition results (including RPPC) for the commercial by industry group, overall commercial, self-haul, single-family and multi-family sectors, and the


TPEPY estimates. Bootstrapping was not used for the overall statewide composition, the residential composition (single-family and multi-family combined), the residential RPPC composition and the overall RPPC composition. Theoretically, resampling methods could have been applied to all the estimates, however, there were computational constraints in terms of computing resources to make it an efficient method to apply at all levels of aggregation. When used for a given statistic, 1000 replicate estimates were calculated, yielding a bootstrap distribution from which the standard errors were derived. Depending on the statistic of interest, the data were resampled with replacement by region, by region and industry group, or by region and sector. BIAS-CORRECTED (BCa) INTERVALS

Ninety percent confidence intervals were calculated for the bootstrap distributions using bias-corrected and adjusted percentiles. The bias-corrected (BCa) method transforms the .5 and .95 probability values to determine which percentiles of the empirical bootstrap distribution most accurately estimate the percentiles of interest. The BCa confidence limits are reported as the lower and upper bounds of the estimates. To be consistent with other reports of this type, “+/-“ values, based on the 90% confidence intervals, were presented with the results. These values were calculated as:

max( , )L UEst CI CI Est− − where max = maximum;

= estimated statistic; EstLCI = lower bootstrap BCa confidence bound; and,

UCI = upper bootstrap BCa confidence bound. Given that most of the bootstrapped confidence intervals were not symmetric, due to the skewness in the resulting bootstrap distributions, the reported “+/-“ value will tend to inflate the confidence interval on one side (usually the lower bound in these analyses). VARIANCE OF SUMS In order to calculate estimates for overall statewide compositions and overall residential compositions, including RPPC estimates, results from multiple survey methods were averaged together as weighted sums. In all cases, the weights were based on the proportion of the waste stream represented by each sector. The proportions were taken from the vehicle survey results. For the purpose of standard error calculations, the individual components were assumed to be independent and the proportions (weights) were treated as constants. The basic formulation was as follows:

2 21 2 1 2( ...) ( ) ( ) ...Var c A c B c Var A c Var B+ + = + +

The decision to treat the proportions as constants was based on the belief that the vehicle survey results provided reliable estimates of the contribution of each sector to the overall waste generated in the state. The numbers from the vehicle survey were used to scale-up the TPEPY estimates and to generate tonnage estimates. While there is some uncertainty associated with the proportion estimates, the impact on standard error estimates of the


weighted averages are likely to be minimal. The proportions are constrained to sum to one, and thus if one goes up, one or more others must go down. Unless the individual standard errors associated with each component are highly variable, the incorporation of the uncertainty in the proportions would likely cancel one another and thus be negligible in an overall standard error estimation. LARGE-SAMPLE CONFIDENCE INTERVALS BASED ON NORMAL THEORY

Confidence intervals for the residential sector (single-family plus multi-family) and the overall statewide compositions were obtained employing normal theory. The general calculation is:

90%, .1(2),k kCI t Var∞= where = 2-sided t-test statistic with .05 in each tail, for.1(2),t ∞ ∞ degrees of freedom

(i.e. assume a normal distribution); kVar = variance of a given estimate, for industry group , for which a confidence

interval is being calculated. k

A.10.6 RPPC STUDY

Prior to calculating the RPPC percent composition figures, the RPPC values within each sample were adjusted to reflect the “clean” weight of the actual plastic, as opposed to the “dirty” weight of plastic contaminated by food and other materials. Contamination rates from the 1995 study of RPPC quantities in California’s waste stream were applied individually to the recorded RPPC weights within each sample. Specific decontamination factors were used for each RPPC material type and for each major sector of the waste stream (commercial, residential, and self-haul). (See Section 3.6.2 of the Final Report.) For each sample, the difference between the measured “dirty” weight of each RPPC material and the calculated “clean” weight was considered to be contamination. The weight of the contamination was added to the weight of all non-RPPC materials in the sample to produce a category that represented everything that was not an RPPC. From this point on, the percent and tons of RPPCs in each waste sector were calculated in a method identical to that described for the regular waste composition calculations described in the sections above. Percent and tonnage estimates were derived for each of eight categories of RPPC, as well as for a ninth category that represented all non-RPPC materials plus contamination.


APPENDIX B: LIST AND DEFINITIONS OF

MATERIAL TYPES

The list and definitions of the Standard Material Categories were drawn from the California Integrated Waste Management Board’s Uniform Waste Disposal Characterization Method.

B.1 LIST OF STANDARD MATERIAL CATEGORIES

The list below shows a hierarchy of material classes and subclasses. As part of the Statewide Waste Characterization Study, solid waste was sorted into the 57 specific material categories shown in bold type, and composition percentages were calculated for those material categories.

Paper

Uncoated Corrugated Cardboard and Paper Bags

1 Uncoated Corrugated Cardboard 2 Paper Bags 3 Newspaper Office Paper

4 White Ledger 5 Colored Ledger 6 Computer Paper 7 Other Office Paper Miscellaneous Paper

8 Magazines and Catalogs 9 Phone Books and Directories

10 Other Miscellaneous Paper 11 Remainder/Composite Paper

Glass

12 Clear Glass Bottles and Containers Colored Glass Bottles and Containers

13 Green Glass Bottles and Containers 14 Brown Glass Bottles and Containers 15 Other Colored Glass Bottles and Containers 16 Flat Glass 17 Remainder/Composite Glass

Metal

Ferrous Metals

18 Tin/Steel Cans 19 Major Appliances 20 Other Ferrous

Non-Ferrous Metals

21 Aluminum Cans 22 Other Non-Ferrous 23 Remainder/Composite Metal

California 1999 Statewide B - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

Plastic

Plastic Containers

24 HDPE Containers 25 PETE Containers 26 Miscellaneous Plastic Containers 27 Film Plastic 28 Durable Plastic Items 29 Remainder/Composite Plastic

Other Organic

30 Food Landscape and Agricultural

31 Leaves and Grass 32 Prunings and Trimmings 33 Branches and Stumps 34 Agricultural Crop Residues

Miscellaneous Organic

35 Manures 36 Textiles 37 Remainder/Composite Organic

Construction and Demolition

38 Concrete 39 Asphalt Paving 40 Asphalt Roofing 41 Lumber 42 Gypsum Board 43 Rock, Soil and Fines 44 Remainder/Composite Construction and Demolition

Household Hazardous Waste

45 Paint 46 Vehicle and Equipment Fluids 47 Used Oil 48 Batteries 49 Remainder/Composite Household Hazardous

Special Waste

50 Ash 51 Sewage Solids 52 Industrial Sludge 53 Treated Medical Waste 54 Bulky Items 55 Tires 56 Remainder/Composite Special Waste 57 Mixed Residue


B.2 DEFINITIONS OF STANDARD MATERIAL CATEGORIES

PAPER "Uncoated Corrugated Cardboard and Paper Bags" includes the two subtypes described

below. The subtypes are "uncoated corrugated cardboard" and "paper bags". (1) Uncoated Corrugated Cardboard usually has three layers. The center wavy

layer is sandwiched between the two outer layers. It does not have any wax coating on the inside or outside.

Examples: This subtype includes entire cardboard containers, such as shipping

and moving boxes, computer packaging cartons, and sheets and pieces of boxes and cartons. This subtype does not include chipboard.

(2) Paper Bags means bags and sheets made from kraft paper. Examples: This subtype includes paper grocery bags, fast food bags, department

store bags, and heavyweight sheets of kraft packing paper. (3) Newspaper means paper used in newspapers. This type does not include any subtypes. Examples: This type includes newspaper and glossy inserts, and all items made from

newsprint, such as free advertising guides, election guides, and tax instruction booklets. "Office Paper" includes the four subtypes described below. The subtypes are "white

ledger", "colored ledger", "computer paper", and "other office paper". (4) White Ledger means uncolored bond, rag, or stationary grade paper. It may

have colored ink on it. When the paper is torn, the fibers are white. Examples: This subtype includes white photocopy, white laser print, and letter

paper. (5) Colored Ledger means colored bond, rag, or stationery grade paper. When the

paper is torn, the fibers are colored throughout. Examples: This subtype includes colored photocopy and letter paper. This

subtype does not include fluorescent dyed paper or deep-tone dyed paper such as goldenrod colored paper.

(6) Computer Paper means paper used for computer printouts. This subtype usually

has a strip of formfeed holes along two edges. If there are no holes, then the edges show tear marks. This subtype can be white or striped.

Examples: This subtype includes computer paper and printouts from continuous

feed printers. This subtype does not include "white ledger" used in laser or impact printers, nor computer paper containing groundwood.

(7) Other Office Paper means other kinds of paper used in offices.


Examples: This subtype includes manila folders, manila envelopes, index cards, white envelopes, white window envelopes, notebook paper, and carbonless forms. This subtype does not include "white ledger", "colored ledger" or "computer paper".

"Miscellaneous Paper" includes the three subtypes described below. The subtypes are

"magazines and catalogs", "phone books and directories", and "other miscellaneous paper".

(8) Magazines and Catalogs means items made of glossy coated paper. This paper

is usually slick, smooth to the touch, and reflects light. Examples: This subtype includes glossy magazines, catalogs, brochures and

pamphlets. (9) Phone Books and Directories means thin paper between coated covers. These

items are bound along the spine with glue. Examples: This subtype includes whole or damaged telephone books, "yellow

pages", real estate listings, and some non-glossy mail order catalogs. (10) Other Miscellaneous Paper means items made mostly of paper that do not fit

into any of the above subtypes. Paper may be combined with minor amounts of other materials such as wax or glues. This subtype includes items made of chipboard, groundwood paper, and deep-toned or fluorescent dyed paper.

Examples: This subtype includes cereal and cracker boxes, unused paper plates

and cups, goldenrod colored paper, hardcover and softcover books, school construction paper, butcher paper, and unopened junk mail.

(11) Remainder/Composite Paper means items made mostly of paper but combined with

large amounts of other materials such as wax, plastic, glues, foil, food, and moisture. Examples: This type includes waxed corrugated cardboard, aseptic packages, wax

coated milk cartons, waxed paper, tissue, paper towels, blueprints, sepia, onion skin, fast food wrappers, carbon paper, self adhesive notes, and photographs.

GLASS (12) Clear Glass Bottles and Containers means clear glass beverage and food containers

with or without a CRV label. Examples: This type includes whole or broken clear soda and beer bottles, fruit juice

bottles, peanut butter jars, and mayonnaise jars. "Colored Glass Bottles and Containers" includes food and beverage containers three

subtypes described below. The subtypes are "green glass bottles and containers", "brown glass bottles", and "other colored containers".

(13) Green Glass Bottles and Containers means green-colored glass containers

with or without a CRV label.


Examples: This subtype includes whole or broken green soda and beer bottles, and whole or broken green wine bottles.

(14) Brown Glass Bottles and Containers means brown-colored glass containers

with or without a CRV label. Examples: This subtype includes whole or broken brown soda and beer bottles,

and whole or broken brown wine bottles. (15) Other Colored Glass Bottles and Containers means colored glass containers

and bottles other than green or brown with or without a CRV label. Examples: This subtype includes whole or broken blue or other colored bottles

and containers. (16) Flat Glass means clear or tinted glass that is flat. This type does not include any

subtypes. Examples: This type includes glass window panes, doors, and table tops, flat automotive

window glass (side windows), safety glass, and architectural glass. This subtype does not include windshields, laminated glass, or any curved glass.

(17) Remainder/Composite Glass means glass that cannot be put in any other type or

subtype. It includes items made mostly of glass but combined with other materials. This type does not include any subtypes.

Examples: This type includes Pyrex, Corningware, crystal and other glass tableware,

mirrors, auto windshields, and light bulbs. METAL The type "ferrous metals" includes three subtypes described below. The subtypes are

"tin/steel cans", "major appliances", and "other ferrous". (18) Tin/Steel Cans means rigid containers made mainly of steel. These items will

stick to a magnet and may be tin-coated. This subtype is used to store food, beverages, paint, and a variety of other household and consumer products.

Examples: This subtype includes canned food and beverage containers, empty

metal paint cans, empty spray paint and other aerosol containers, and bimetal containers with steel sides and aluminum ends.

(19) Major Appliances means discarded major appliances of any color. These items

are often enamel-coated. Examples: This subtype includes washing machines, clothes dryers, hot water

heaters, stoves, and refrigerators. This subtype does not include electronics, such as televisions and stereos.

(20) Other Ferrous means any iron or steel that is magnetic or any stainless steel

item. This subtype does not include "tin/steel cans".


Examples: This subtype includes structural steel beams, metal clothes hangers,

metal pipes, stainless steel cookware, security bars, and scrap ferrous items. "Non-Ferrous Metals" includes the two subtypes described below. The subtypes are

"Aluminum Cans" and "Other Non-Ferrous". (21) Aluminum Cans means any food or beverage container made mainly of

aluminum. Examples: This subtype includes aluminum soda or beer cans, and some pet

food cans. This subtype does not include bimetal containers with steel sides and aluminum ends.

(22) Other Non-Ferrous means any metal item, other than aluminum cans, that is not

stainless steel and that is not magnetic. These items may be made of aluminum, copper, brass, bronze, lead, zinc, or other metals.

Examples: This subtype includes aluminum window frames, aluminum siding,

copper wire, shell casings, brass pipe, and aluminum foil. (23) Remainder/Composite Metal means metal that cannot be put in any other type or

subtype. This type includes items made mostly of metal but combined with other materials and items made of both ferrous metals and non-ferrous metal combined. This type does not include any subtypes.

Examples: This type includes brown goods (electronics and other small appliances),

computers, televisions, radios, and electronic parts. PLASTIC "Plastic Containers" includes the three subtypes described below. The subtypes are

"HDPE Containers" "PETE Containers", and "Other Plastic Containers". (24) HDPE Containers means natural and colored HDPE containers. This plastic is

usually either cloudy white, allowing light to pass through it (natural) or a solid color, preventing light from passing through it (colored). When marked for identification, it bears the number "2" in the triangular recycling symbol.

Examples: This subtype includes milk jugs, water jugs, detergent bottles, some

hair-care bottles, empty motor oil, empty antifreeze, and other empty vehicle and equipment fluid containers.

(25) PETE Containers means clear or colored PETE containers. When marked for

identification, it bears the number "1" in the center of the triangular recycling symbol and may also bear the letters "PETE" or "PET". The color is usually transparent green or clear. A PETE container usually has a small dot left from the manufacturing process, not a seam. It does not turn white when bent.

Examples: This subtype includes soft drink and water bottles, some liquor

bottles, cooking oil containers, and aspirin bottles.


(26) Miscellaneous Plastic Containers means plastic containers made of types of

plastic other than HDPE or PETE. Items may be made of PVC, PP, or PS. When marked for identification, these items may bear the number "3", "4", "5", "6", or "7" in the triangular recycling symbol.

Examples: This subtype includes food containers such as bottles for salad

dressings and vegetable oils, flexible and brittle yogurt cups, syrup bottles, margarine tubs, microwave food trays, clamshell-shaped fast food or muffin containers, and foam egg cartons. This subtype also includes some shampoo containers and vitamin bottles.

(27) Film Plastic means flexible plastic sheeting. It is made from a variety of plastic resins

including HDPE and LDPE. It can be easily contoured around an object by hand pressure. This type does not include any subtypes.

Examples: This type includes plastic garbage bags, food bags, dry cleaning bags,

grocery store bags, packaging wrap, and food wrap. This type does not include rigid bubble packaging.

(28) Durable Plastic Items means plastic objects other than containers and film plastic. This

type also includes plastic objects other than containers or film that bear the numbers "1" through "7" in the triangular recycling symbol. These items are usually made to last for more than one use.

Examples: This type includes plastic outdoor furniture, plastic toys and sporting goods,

and plastic housewares, such as mop buckets, dishes, cups, and cutlery. This type also includes building materials such as house siding, window sashes and frames, housings for electronics such as computers, televisions and stereos, and plastic pipes and fittings.

(29) Remainder and Composite Plastic means plastic that cannot be put in any other type

or subtype. This type includes items made mostly of plastic but combined with other materials. This type does not include any subtypes.

Examples: This type includes auto parts made of plastic attached to metal, plastic

bubble packaging, drinking straws, foam drinking cups, produce trays, foam packing blocks, packing peanuts, foam plates and bowls, plastic strapping, plastic lids, and new plastic laminate (e.g., Formica), vinyl, and linoleum.

OTHER ORGANIC (30) Food means food material resulting from the processing, storage, preparation, cooking,

handling or consumption of food. This type includes material from industrial, commercial or residential sources. This type does not include any subtypes.

Examples: This type includes discarded meat scraps, dairy products, egg shells, fruit or

vegetable peels, and other food items from homes, stores, and restaurants. This type includes grape pomace and other processed residues or material from canneries, wineries, or other industrial sources.


"Landscape and Agricultural" includes the four subtypes described below. The subtypes are "Leaves and Grass", "Prunings and Trimmings", "Branches and Stumps", and "Agricultural Crop Residues".

(31) Leaves and Grass means plant material, except woody material, from any public

or private landscapes. Examples: This subtype includes leaves, grass clippings, and plants. This

subtype does not include woody material or material from agricultural sources. (32) Prunings and Trimmings means woody plant material up to 4 inches in

diameter from any public or private landscape. Examples: This subtype includes prunings, shrubs, and small branches with

branch diameters that do not exceed 4 inches. This subtype does not include stumps, tree trunks, or branches exceeding 4 inches in diameter. This subtype does not include material from agricultural sources.

(33) Branches and Stumps means woody plant material, branches and stumps that

exceed 4 inches in diameter from any public or private landscape. (34) Agricultural Crop Residues means plant material from agricultural sources. Examples: This subtype includes orchard and vineyard prunings, vegetable

by-products from farming, residual fruits, vegetables, and other crop remains after usable crop is harvested. This subtype does not include processed residues from canneries, wineries, or other industrial sources.

"Miscellaneous Organic" includes two subtypes described below. The subtypes are

"Manures" and "Textiles". (35) Manures means manure and soiled bedding materials from domestic, farm, or

ranch animals. Examples: This subtype includes manure and soiled bedding from animal

production operations, race-tracks, riding stables, animal hospitals, and other sources.

(36) Textiles means items made of thread, yarn, fabric, or cloth. Examples: This subtype includes clothes, fabric trimmings, draperies, and all

natural and synthetic cloth fibers. This subtype does not include cloth covered furniture, mattresses, leather shoes, leather bags, or leather belts.

(37) Remainder/Composite Organic means organic material that cannot be put in any other

type or subtype. This type includes items made mostly of organic materials but combined with other materials. This type does not include any subtypes.

Examples: This type includes leather items, carpets, cork, hemp rope, garden hoses,

rubber items, hair, carpet padding, cigarette butts, disposable diapers, feminine hygiene products, and animal feces.


CONSTRUCTION AND DEMOLITION (38) Concrete means a hard material made from sand, gravel, aggregate, cement mix and

water. Examples: This subtype includes pieces of building foundations, concrete paving, and

cinder blocks. (39) Asphalt Paving means a black or brown, tar-like material mixed with aggregate used as

a paving material. (40) Asphalt Roofing means composite shingles and other roofing material made with

asphalt. Examples: This type includes asphalt shingles and attached roofing tar and tar paper. (41) Lumber means processed wood for building, manufacturing, landscaping, packaging,

and processed wood from demolition. This type does not include any subtypes. Examples: This type includes dimensional lumber, lumber cutoffs, engineered wood

such as plywood and particleboard, wood scraps, pallets, wood fencing, wood shake roofing, and wood siding.

(42) Gypsum Board means interior wall covering made of a sheet of gypsum sandwiched

between paper layers. Examples: This subtype includes used or unused, broken or whole sheets of sheetrock,

drywall, gypsum board, plasterboard, gypboard, gyproc, and wallboard. (43) Rock, Soil and Fines means rock pieces of any size and soil, dirt, and other matter. Examples: This subtype includes rock, stones, and sand, clay, soil and other fines. This

subtype also includes non-hazardous contaminated soil. (44) Remainder/Composite Construction and Demolition means construction and

demolition material that cannot be put in any other type or subtype. This type may include items from different categories combined, which would be very hard to separate. This type does not include any subtypes.

Examples: This type includes brick, ceramics, tiles, toilets, sinks, and fiberglass

insulation. This type may also include demolition debris that is a mixture of items such as plate glass, wood, tiles, gypsum board, and aluminum scrap.

HOUSEHOLD HAZARDOUS WASTE (45) Paint means containers with paint in them. This type does not include any subtypes. Examples: This type includes latex paint, oil based paint, and tubes of pigment or fine art

paint. This type does not include dried paint, empty paint cans, or empty aerosol containers.


46) Vehicle and Equipment Fluids means containers with fluids used in vehicles or engines, except used oil. This type does not include any subtypes.

Examples: This type includes used antifreeze and brake fluid. This type does not include

empty vehicle and equipment fluid containers. (47) Used Oil means the same as defined in Health and Safety Code section 25250.1(a).

This type does not include any subtypes. Examples: This type includes spent lubricating oil such as crankcase and transmission

oil, gear oil, and hydraulic oil. (48) Batteries means any type of battery including both drycell and lead acid. This type does

not include any subtypes. Examples: This type includes car, flashlight, small appliance, watch and hearing aid

batteries. (49) Remainder/Composite Household Hazardous means household hazardous material

that cannot be put in the "Paint", "Automotive Fluids", "Used Oil", or "Batteries" subtypes. This type also includes household hazardous material that is mixed. This type does not include any subtypes.

Examples: This type includes household hazardous waste which if improperly put in the

solid waste stream may present handling problems or other hazards. SPECIAL WASTE (50) Ash means a residue from the combustion of any solid or liquid material. This type does

not include any subtypes. Examples: This type includes ash from fireplaces, incinerators, biomass facilities, waste-

to-energy facilities, and barbecues. This subtype also includes ash and burned debris from structure fires.

(51) Sewage Solids means residual solids and semi-solids from the treatment of domestic

waste water or sewage. This type does not include any subtypes. Examples: This type includes biosolids, sludge, grit, screenings, and septage. This

subtype does not include sewage or waste water discharged from the sewage treatment process.

(52) Industrial Sludge means sludge from factories, manufacturing facilities, and refineries.

This type does not include any subtypes. Examples: This type includes paper pulp sludge, and water treatment filter cake sludge. (53) Treated Medical Waste has the same meaning as treated medical waste in Section

25023.5 of the Health and Safety Code. This type does not include any subtypes.


(54) Bulky Items means large hard to handle items that are not defined separately, including furniture, mattresses, and other large items. This type does not include any subtypes.

Examples: This type includes all sizes and types of furniture, mattresses, box springs,

and base components. (55) Tires means vehicle tires. This type does not include any subtypes. Examples: This type includes tires from trucks, automobiles, motorcycles, heavy

equipment, and bicycles. (56) Remainder/Composite Special Waste means special waste that cannot be put in any

other type. Examples: This type includes asbestos-containing materials, such as certain types of

pipe insulation and floor tiles, auto fluff, auto-bodies, trucks, trailers, truck cabs, and artificial fireplace logs.

MIXED RESIDUE (57) Mixed Residue means material that cannot be put in any other type or subtype in the

other categories. This category includes mixed residue that cannot be further sorted. This category does not include any types or subtypes.

Examples: This type includes residual material from a materials recovery facility or other

sorting process that cannot be put in any of the previous remainder/composite types.


B.3 LIST AND EXAMPLES OF RPPCS

In addition to classifying all materials according to the 57 material categories, the contractor classified RPPCs (Rigid Plastic Packaging Containers) from each sample into the eight categories listed below.

RPPC Material Description and Examples

1 #1 PET Soda Bottles PET bottles containing carbonated beverages such as soda pop, some sports drinks, or sparkling waters.

2 #1 PET Custom Bottles PET bottles containing anything that is not a carbonated beverage. Examples include cooking oil bottles, shampoo bottles, and some liquor bottles.

3 #1 PET Non-Bottle Rigids PET packages that are recloseable, such as packages containing small toys or hardware items.

4 #2 HDPE Natural Bottles Primarily milk jugs and some juice bottles.

5 #2 HDPE Colored Bottles Any HDPE bottle that is not clear/translucent. Examples include some orange juice bottles, many laundry detergent bottles, and some shampoo bottles.

6 #2 HDPE Other Containers Examples include paint buckets, some margarine containers, some food jars, and some yogurt containers.

7 All Other RPPC Bottles All plastic bottles that are not PET or HDPE. Examples include some sports drink bottles, many shampoo bottles, and some detergent bottles.

8 All Other RPPC Non-Bottles Includes containers for some prepared foods, such as chip dip. Also includes some yogurt and margarine containers, as well as polystyrene egg cartons.

A container must meet all of the following criteria to be considered an RPPC.

•

•

•

•

•

•

It is made entirely of plastic, except that lids, caps, or labels may be made of some other material.

It is capable of maintaining its shape while holding a product.

It is capable of multiple re-closure, with an attached or unattached lid or cap.

Contains at least eight fluid ounces but no more than five gallons, or the equivalent volumes.

It is normally used to store a product for seven days or longer (i.e., from the time the containers are filled).

It is a packaging container in which a product is sold, offered for sale or distributed in California.


APPENDIX C: CIWMB STANDARD METHOD

C.1 DRAFT REGULATIONS GOVERNING DISPOSAL CHARACTERIZATION STUDIES

CALIFORNIA INTEGRATED WASTE MANAGEMENT BOARD PRELIMINARY DRAFT REGULATIONS – NOVEMBER 13, 1996

DISPOSAL CHARACTERIZATION STUDIES <Note: The following proposed text would add Article 6.0 to Title 14, California Code of

Regulations, Division 7, Chapter 9.>

California Code of Regulations, Title 14, Division 7, Chapter 9 ARTICLE 6.0 DISPOSAL CHARACTERIZATION STUDIES Section DETAILED ANALYSIS 18726.0 Requirements for Conducting Disposal Characterization Studies 18726.1 General Information for Disposal Characterization Studies 18726.2 Determining Objectives and Scope of the Disposal Characterization Study 18726.3 Determining Data Collection Approach And Study Design 18726.10 Using Default Data for Disposal Characterization Studies 18726.20 Using Existing Data for Disposal Characterization Studies 18726.30 General Requirements for Conducting Landfill Sampling or Generator

Sampling 18726.32 Health and Safety for Landfill Sampling or Generator Sampling 18726.34 Using Standard Sampling Protocols for Landfill Sampling or Generator

Sampling 18726.40 Specific Requirements for Conducting Landfill Sampling 18726.45 Data Analysis for Landfill Sampling 18726.50 Specific Requirements for Conducting Generator Sampling 18726.52 Sample Selection for Generator Sampling 18726.54 Data Analysis for Generator Sampling 18726.60 Use of Alternatives to the Minimum Requirements for Landfill and

Generator Sampling 18726.70 Combining Data Collection Approaches 18726.90 Reporting Requirements

California 1999 Statewide C - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

ARTICLE 6.0 DISPOSAL CHARACTERIZATION STUDIES Section 18726.0 Requirements for Conducting Disposal Characterization Studies (a) Disposal Characterization Studies (DC studies) are generally conducted to collect

information on the types and amounts of materials in the disposed waste stream. This information can be used to plan programs to divert solid waste from disposal. A jurisdiction shall conduct a DC study when:

(1) The Board has given the jurisdiction specific direction to conduct a DC Study,

pursuant to Section 41770(b) of the Public Resources Code, because the jurisdiction has not met the 25% or 50% disposal reduction goal stated in Section 41780 of the Public Resources Code, or an alternative goal as approved by the Board;

(2) The jurisdiction will be revising its SRRE pursuant to Section 18788 of this

Chapter and intends to include new disposal characterization information in the revision.

(b) The Uniform Waste Disposal Characterization Method, as specified in these

regulations, shall be used by jurisdictions when conducting DC Studies. A DC Study shall constitute the Waste Characterization Component of a revised SRRE required by Sections 41030, 41032, 41330, and 41332 of the Public Resources Code.

(c) Jurisdictions conducting studies for purposes other than meeting the requirements of

Section 18726.0(a) may use a method other than the Uniform Waste Disposal Characterization Method and need not include the resulting information in a revised SRRE. The information may be submitted as an appendix to the Waste Characterization Component, or in another Component of a revised SRRE.

NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.1 General Information for Disposal Characterization Studies (a) A DC Study included in a revised SRRE is different from a Solid Waste Generation

Study (SWGS) required to be included in an initial SRRE. Requirements for a SWGS are included in Article 5.0 of this Chapter, commencing with Section 18722.0.

(b) DC studies shall include the following five steps:

(1) select a characterization approach as specified in Sections 18726.2 and 18726.3 of this Article;

(2) collect data that is statistically representative of the jurisdiction as specified in

Sections 18726.10, 18726.20, 18726.40 and 18726.50 of this Article;


(3) when sampling studies are conducted, use standard field protocols pursuant to Sections 18726.30 and 18726.34 of this Article;

(4) when sampling studies are conducted, use minimum health and safety

standards pursuant to Section 18726.32 of this Article; (5) when sampling studies are conducted, use standard data analysis methods

pursuant to Sections 18726.45 and 18726.54 of this Article. (c) Definitions which apply to this entire Chapter can be found in Article 3.0 of this

Chapter (commencing with Section 18720.0). Definitions which apply specifically to DC Studies can be found in Section 18720.9 of Article 3.0 of this Chapter.

(d) Jurisdictions shall use the standard material type definitions found in Article 4.0 of

this Chapter, commencing with Section 18721.0, when collecting information on their waste stream for a DC study.

(e) Reporting requirements for DC studies are found in Section 18726.90 of this Article. (f) Jurisdictions may work together to conduct a DC study. The DC study shall

characterize solid waste disposed from the participating jurisdictions. Waste characterization data shall be collected for each individual jurisdiction. Each participating jurisdiction shall individually follow the requirements of Sections 18726.2, 18726.3, and 18726.90 of this Article, and shall collect data that is statistically representative of the individual jurisdiction.

(g) Regional agencies, approved by the Board pursuant to Section 40975 of the Public

Resources Code, may conduct a DC study to characterize waste from within the regional agency. The data collected must be statistically representative of the regional agency. Data for each member jurisdiction does not need to be reported by the regional agency. A city, county, or city and county, which has become a member of a regional agency, may prepare and submit to the Board an individual DC study, separate from that of the regional agency of which it is a member.

NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.2 Determining Objectives and Scope of the Disposal

Characterization Study (a) To determine the objectives of the DC study, jurisdictions shall consider the following

factors.

(1) Any conditions set by the Board if required to conduct a DC Study because diversion goals have not been met.

(2) New or updated information the jurisdiction intends to include in a revised

SRRE, excluding revisions to base-year quantity data as described in an


Annual Report prepared pursuant to Article 9.0 of this Chapter commencing with Section 18794.0.

(3) Intended use of waste characterization data, such as planning diversion

programs, facility design, monitoring diversion program success, determining changes in waste stream characteristics, or other uses. The jurisdiction shall consider the data uses as related to program planning to meet disposal reduction goals.

(4) Any other factors the jurisdiction deems important.

(b) To determine the scope of the DC study, jurisdictions shall consider the following

factors.

(1) Resources available for collecting waste characterization data, such as funding, staff time and expertise, or other resources. The tables in Sections 18726.40 and 18726.50 may be used to evaluate resource needs for DC sampling studies.

(2) Degree of accuracy and reliability of the data needed to satisfy the intended

uses. Some data uses may require greater accuracy than can be achieved by use of the minimum standards described in these regulations.

(3) Whether information on material types shall be collected at the type or

subtype level using the Material Type Definitions pursuant to Article 4.0 of this Chapter commencing with Section 18721.0.

(4) The extent of the data collection (i.e., comprehensive v. targeted studies)

needed to satisfy the intended uses, and the sector(s), subpopulation(s), or other portion(s) of the waste stream to be included in the DC study such as the residential sector waste stream or the waste stream from a specific business grouping (subpopulation).

(5) Seasonal factors that affect the waste stream being characterized, such as

those specified in Section 18726.45(c) of this Article.

(6) Special or unique waste streams that may need to be considered, such as self-haul, construction and demolition waste, biosolids, or disaster-related waste.

(7) Any other factors the jurisdiction deems important.

(c) The factors listed in this Section shall be used by the jurisdiction to determine the

data collection approach as described in Section 18726.2 of this Article. NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code.


Section 18726.3 Determining Data Collection Approach and DC Study Design (a) The jurisdiction shall select one or more characterization approach(es) (i.e., how

data will be collected) from the following:

(1) Use of default data from the CIWMB Waste Characterization Database. Jurisdictions may use default waste characterization data provided by the Board from the CIWMB Waste Characterization Database to collect information on their waste streams for diversion program planning. The requirements for using default data are found in Section 18726.10 of this Article.

(2) Use of existing data. Jurisdictions may use past studies conducted on their

waste streams, or studies conducted by other jurisdictions, to collect information for diversion program planning. Jurisdictions may combine information from more than one existing study. The requirements for using existing data are found in Section 18726.20 of this Article.

(3) Landfill sampling or disposal facility sampling. Portions of waste (samples)

are taken from trucks delivering waste to a facility such as a landfill, transfer station, or transformation facility. This approach is generally used to collect data at the sector level, such as for the residential sector or non-residential sector of a jurisdiction. The requirements for conducting landfill sampling studies are found in Sections 18726.30, 18726.32, 18726.34, 18726.40, and 18726.45 of this Article.

(4) Waste generator sampling. Portions of waste (samples) are collected directly

from generators (such as individual residences or businesses) before the waste has been mixed with waste from other generators. This usually means samples are taken from individual bins before the waste is picked up by a collection vehicle. Waste characterization data can then be traced to a specific type of generator. Waste generator sampling is generally used to collect data for specific generators or groups of generators, such as similar types of businesses or residences. The requirements for conducting generator sampling studies are found in Sections 18726.30, 18726.32, 18726.34, 18726.50, 18726.52, and 18726.54 of this Article.

(5) Combination of approaches described in this Section, where appropriate. The

requirements for combining approaches are found in Section 18726.70 of this Article.

(b) For a targeted waste type, such as household hazardous waste, or a targeted group

of waste generators, jurisdictions may use a mass balance or materials flow data collection approach. This approach shall only be used if the jurisdiction determines it is the best way to collect the specific data needed. With a mass balance method, information on a jurisdiction's waste stream is developed by using data on quantities of commodities sold in the jurisdiction's marketplace. This data is used to estimate


solid wastes disposed as a result of the sale of these commodities. The jurisdiction shall, in the Waste Characterization Component of the SRRE, explain why this approach was chosen, and describe how the mass balance DC study was designed and conducted.

(c) If the factors listed in Section 18726.2 indicate one particular approach described in

this section to be most appropriate, but the jurisdiction prefers to use another approach described in this section, it shall explain in the Waste Characterization Component of the SRRE how the preferred approach still meets the needs of the data collection effort and/or any specific direction given by the Board.

NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.10 Using Default Data For Disposal Characterization Studies (a) The Board’s default data incorporated into the CIWMB Waste Characterization

Database includes the following information:

(1) disposal compositions for the business subpopulations listed in Appendix 3, which is hereby incorporated by Reference. These are based on statewide average data from generator-based waste characterization studies;

(2) statewide average disposal correlative factors for the subpopulations listed in

Appendix 3, which relate the tons of waste disposed per employee per year;

(3) the numbers and types of businesses in each jurisdiction, and the number of employees in each subpopulation listed in Appendix 3 in the jurisdiction, based on a commercially-available business information database;

(4) composition of the disposed residential waste stream, based on a statewide

average composition;

(5) a statewide average disposal correlative factor for the residential waste stream relating tons disposed per resident.

(b) The jurisdiction shall evaluate whether default data provided by the Board will

adequately meet the objectives and scope of the DC study, as determined in Section 18726.2 of this Article.

(c) The jurisdiction shall evaluate whether the default data is applicable to local

conditions such as local diversion programs, climate, economic factors, demographic factors, and other local factors which the jurisdiction determines to be important. The jurisdiction shall consider the following characteristics of the default data in the evaluation:


(1) Default data represents the average of data from all samples characterized in each subpopulation and made available to the Board. The CIWMB Waste Characterization Database makes information from many studies readily available for use by jurisdictions by providing this average data. Composition and disposal correlative factor data is based on samples and other information collected from the disposed waste streams of individual businesses and residences in some jurisdictions in California. Default data reflects the waste patterns and diversion programs existing in those jurisdictions. Jurisdictions using default data shall consider local waste patterns, diversion programs, and other circumstances that may differ from average conditions and may affect applicability of default data for the purposes of the study.

(2) Waste patterns within a subpopulation in a particular jurisdiction may vary

from the average, due to the different sizes and types of businesses included in the local subpopulation.

(3) The numbers and types of businesses in a jurisdiction may change rapidly

and this may not be accurately reflected in default data. (d) DC studies using default data will be considered statistically representative if the

jurisdiction demonstrates that default data meets the objectives and scope of the DC study, and is applicable to local conditions according to the evaluation required by this Section. If the evaluation shows that the addition of local data is needed to increase the applicability of default data to local conditions, and local data is available, the default data may be modified to include data on local conditions.

(e) The jurisdiction shall briefly explain, in its Waste Characterization Component of a

revised SRRE, the applicability of default data to the local conditions, how it was evaluated, and how it was used to meet the scope and purpose of the DC study. If default data was modified to better reflect local conditions, this shall also be described in the Waste Characterization Component.

NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.20 Using Existing Data for Disposal Characterization Studies (a) A jurisdiction may use past studies conducted on its waste stream, or studies

conducted on the waste streams of other jurisdictions, to collect information for a DC study. A jurisdiction may combine information from more than one existing study.

(b) The existing data used shall not be more than 5 years old. (c) The jurisdiction shall evaluate whether the existing data is compatible with the

objectives and scope of the DC study as determined by Section 18726.2 of this


Article, and is specific and accurate enough to accomplish the purpose of the new DC study.

(d) When using existing data from another jurisdiction, the jurisdiction shall show that the

other jurisdiction is comparable because of similarities between the sources of disposal.

(1) When using residential data from a comparable jurisdiction, the jurisdiction

shall compare characteristics of the residential sector that affect the subtypes and amounts of solid waste disposed. Examples of characteristics that may affect the subtypes and amounts of residential solid waste include: population, population density, income, lot size, percent of single family homes v. multi-family, amount of rural area v. urban area, education level, amount of mandatory collection of waste v. self-haul, type of disposal collection, disposal fees (variable can rates, self-haul fees), availability and convenience of diversion programs, or climate.

(2) When using non-residential data from a comparable jurisdiction, the

jurisdiction shall compare characteristics of the non-residential sector that affect the subtypes and amounts of solid waste disposed. Examples of characteristics that may affect the subtypes and amounts of non-residential solid waste include: numbers and types of commercial and industrial businesses, relative proportions of business types, sizes of businesses, number of employees at different businesses, building density, taxable sales, types of products sold, amount of rural area v. urban area, amount of mandatory collection of waste v. self-haul, type of disposal collection, disposal fees (variable can rates, self-haul fees), availability and convenience of diversion programs, or climate.

(3) The jurisdiction shall describe the characteristics that are similar, and the

characteristics that are different, between the two jurisdictions that affect the subtypes and amounts of solid waste disposed for each source characterized. This information shall be included in the Waste Characterization Component of a revised SRRE, and shall include relevant numerical information that is commonly available.

(e) The existing data used must be statistically representative of the jurisdiction. DC

studies based on use of existing data will be considered to meet this if one of the following conditions is met:

(1) The existing data comes from studies which meet the criteria specified in

Sections 18726.40 and 18726.50 of this Article, and the data comes from the jurisdiction itself or from a comparable jurisdiction.

(2) The existing data meets the requirements of this Article.

(3) Other data which does not meet the criteria of this Section may be acceptable

if the jurisdiction can show that it is statistically representative based on other


criteria, and approved by Board staff prior to use, on a case-by-case basis, as specified in Section 18726.52(f) of this Article.

(4) Jurisdictions may conduct limited sampling to supplement existing data, or

combine data sets, in order to develop a data set that is statistically representative of the jurisdiction.

(f) Waste characterization field studies may have been conducted for the purpose of

revising a SRRE prior to Board approval of the Uniform Waste Disposal Characterization Method. These studies may not meet all the requirements for statistical representativeness specified in Sections 18726.40 and 18726.50 of this Article. Jurisdictions may receive approval to use data from these studies, on a case-by-case basis as described in Section 18726.52(f) of this Article, if the jurisdiction demonstrates that the existing study adequately meets its needs for diversion program planning and evaluation.

(g) The jurisdiction shall, in the Waste Characterization Component of a revised SRRE,

identify the source of existing data used, briefly describe how the data was collected or include the study itself, explain how the data is statistically representative of the jurisdiction, and explain how it meets the objectives and scope of the new DC study, as was identified according to Section 18726.2 of this Article.

NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.30 General Requirements for Conducting Landfill Sampling or

Generator Sampling DC sampling studies may be conducted using landfill sampling or generator sampling, or a combination of both. Health and safety protocol and field protocol requirements are the same for both types of DC studies, as described in Sections 18726.32 and 18726.34 of this Article. Requirements for sample selection, number of samples, sample weights, addressing seasonality, and data analysis are different for landfill and generator sampling, as described in Sections 18726.40 through 18726.54 of this Article. NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.32 Health and Safety for Landfill Sampling or Generator Sampling (a) Before conducting landfill or generator sampling, the local waste characterization

project manager shall assess the health and safety issues associated with each individual sort and establish the appropriate training, procedures, and safeguards. Health and safety measures may include development of local protocols, training and supervision of sorters, designation of an on-site Safety Officer, or other measures.


(b) The jurisdiction shall consider the "Health and Safety Plan for Waste Characterization Studies" included in Appendix 1, which is incorporated by Reference, to help identify and evaluate risks. Every waste characterization study is different, and this Plan cannot identify every possible risk.

(c) The jurisdiction shall briefly list in the Waste Characterization Component of the

SRRE the health and safety measures used for the DC sampling study. NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.34 Using Standard Sampling Protocols for Landfill Sampling or

Generator Sampling (a) Physical or visual sample sorting procedures may be used. Jurisdictions shall

consider the "Physical and Visual Solid Waste Sorting Procedures" included in Appendix 2, which is incorporated by Reference, as a guideline for sorting. Once the sample has been identified, the entire sample should be placed on a clean surface and sorted, either all at once or in stages. Materials should be assigned to waste types or subtypes. The weight or volume of each type or subtype shall be measured for each sample, and from this the percentage of each material type shall be determined for each sample.

(1) Since visual sorting may be prone to more errors of estimation than physical

sorting, quality control measures shall be used to increase accuracy. The jurisdiction shall concisely describe in the Waste Characterization Component of a revised SRRE the quality control measures that were used. Examples of such measures are:

(A) At least 2 people estimate the composition of a sample, and the

average value of each material type is used;

(B) Periodically perform both a visual and physical sort on the same sample, for example every fifth sample. Perform the physical sort after the visual sort, and continually adjust estimation procedures to improve accuracy.

(C) Weighing specific items in the sample when it is difficult to estimate

the item's volume (for example, a broken chair). (b) The sample shall be sorted into standard material types or subtypes, according to

the definitions in Article 4.0 of this Chapter, commencing with Section 18721.0. At a minimum, data shall be collected at the standard material type level. If more detailed data is collected for submission to the Board, the subtype definitions in Article 4.0 of this Chapter, commencing with Section 18721.0 shall be used in place of the material type(s) definitions. The jurisdiction may design other subtypes according to the protocols described in Article 4.0 of this Chapter. The subtype level may be used


for some categories and the type level for other categories, according to the data needs of the jurisdiction.

(c) When sorting materials, sometimes it is unclear which type or subtype materials

should be assigned to, due to contamination or other reasons. If the data from the study will be used to plan diversion programs which involve separating or reducing materials at the source, this general rule shall be used: Items that have the potential to be diverted through waste prevention or source-separated diversion programs shall be classified into higher value material types, and items that have little potential for diversion programs shall be classified in lower value material types.

NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.40 Specific Requirements for Conducting Landfill Sampling (a) As required by Public Resources Code Sections 41032 and 41332, for the data

collected from landfill sampling to be statistically representative of the solid waste disposed by the jurisdiction and to reflect seasonal variation, samples shall be selected according to Table 1. Jurisdictions may collect more samples over more seasons than specified by these minimum requirements.

Table 1. Sample Numbers and Weights for Landfill Sampling.

Type of Disposal Characterization Study

Minimum Number of Samples per Year

Minimum Sample Weight

Landfill Sampling - Residential Sector 30, distributed over a minimum of 2 seasons

200 pounds

Landfill Sampling - Non-Residential Sector 40, distributed over a minimum of 2 seasons

200 pounds

(b) To address seasonal variations that may occur during the calendar year, jurisdictions

shall assess cyclical patterns of local climate, demography, commerce, or other local factors which may affect the composition of the waste stream. Sampling shall occur during a minimum of two seasons, with the number of samples split between the sampling periods, so as to gather the most representative data for the jurisdiction.

(c) Vehicles from which samples are taken shall be chosen randomly. The sampled

portion of the vehicle load shall also be chosen randomly by the grid method or by the cone and quarter method as described in the ASTM Standard Test Method for Determination of the Composition of Unprocessed Municipal Solid Waste, published September 1992, which is incorporated by Reference. The jurisdiction shall verify that the vehicle sampled carries waste from the jurisdiction and sector being characterized.

(d) Only one sample shall be taken from each truck. More than one sample may be

taken from one truck only if the jurisdiction notifies Board staff of the sampling plan


prior to the study, and demonstrates that the data collected will be statistically representative, and:

(1) the number of truckloads available for sampling in one season is less than

20; or

(2) the jurisdiction's study design shows that more than one sample per truck is desirable to achieve the study purpose.

NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.45 Data Analysis for Landfill Sampling For randomly selected samples from a sector taken at a landfill or other disposal facility, the average composition shall be determined. This is done by summing the percentage of the material type in each sample and dividing by the number of samples. The calculation is performed for each material type or subtype characterized. The average percentage of material type, confidence interval at a 90% confidence level, and the standard deviation shall be calculated for each material type. To calculate estimated tonnages of each material type disposed by the sector, the average material type percentage is multiplied by the total tonnage disposed by the sector. NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.50 Specific Requirements for Conducting Generator Sampling (a) For generator sampling, generators shall be made in to groups of similar businesses

or residences. These groups are called subpopulations. An example of a business subpopulation is “retail trade food stores” and an example of a residential subpopulation is “apartment buildings.” Appendix 3 lists business subpopulations that may be used for generator DC studies in the non-residential sector. Generator sampling may be used to characterize entire sectors as well as subpopulations.

(b) As required by Public Resources Code Sections 41032 and 41332, for the data

collected to be statistically representative of the solid waste disposed by the jurisdiction and to reflect seasonal variation, samples shall be selected according to Table 2. Jurisdictions may collect more samples over more seasons than specified by these minimum requirements.


Table 2. Sample Numbers and Weights for Generator Sampling.

Type of Disposal Characterization Study Minimum Number of

Samples Per Year Minimum Sample

Weight Generator Sampling - Residential Sector 40, distributed over a

minimum of 2 seasons 125 lb. or 1.5 CY* or Whole Sample

Generator Sampling - Non-Residential Sector-level Study

50, distributed suitably to reflect seasons

125 lb. or 1.5 CY or Whole Sample

Generator Sampling - Subpopulation Level with Similar Businesses in Subpopulation



Generator Sampling - Subpopulation Level with Different Business in Subpopulation



* CY = cubic yards (c) When the types of businesses grouped together in a subpopulation are different from

each other, more samples should be taken to adequately characterize the variability. Generally, subpopulation numbers 1, 2, 3, 4, 11, 15, 16, 17, 22, 23, 24, 30, and 37 in Appendix 3 are subpopulations with different businesses included in the grouping. Jurisdictions shall evaluate the generators in their jurisdiction which are included in their target subpopulation to determine if they are different enough to require more sampling.

(d) To address seasonal variations that may occur during the calendar year, jurisdictions

shall assess cyclical patterns of local climate, demography, trade, or commerce, or other local factors which may affect the composition of the waste stream being sampled. Sampling should be timed to gather the most representative data for the jurisdiction or the most important data to achieve the purposes of the DC study. For residential generator DC studies, sampling shall occur during a minimum of two seasons, and the number of samples shall be split between the sampling periods.

NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.52 Sample Selection for Generator Sampling (a) For generator DC studies, individual businesses or residences shall be selected for

sampling. The sector or subpopulation being sampled shall be subdivided ("stratified") into sampling groups ("strata") and individual generators shall be chosen from each group. Strata shall be based on criteria affecting waste patterns such as size of business (based on number of employees) or type of residence (multifamily or single family). The number of samples shall be allocated to each strata according to its proportion of the waste stream.

(b) For residential generator sampling studies which include the entire residential sector,

the jurisdiction shall stratify residential generators into single-family residences and multi-family residences. Samples shall be allocated to each strata proportionate to the amount of waste disposed by the strata.


(c) For non-residential generator sampling studies, jurisdictions may use the method for grouping generators which is most appropriate for the intended use of the waste characterization data. The recommended method of stratification and sample allocation is the "80/20 rule." This approach is based on the assumption that 80% of the waste comes from 20% of the businesses (the largest businesses in the group). When using this rule, the sector or subpopulation shall be stratified by size so that the larger businesses that make up 20% of the group are separated from the other 80% of the businesses. The total number of generators to be sampled shall be allocated so that 80% of the samples are randomly assigned to businesses in the large generator group, and the remaining 20% of the samples are randomly assigned to the remaining businesses (which generate 20% of the waste).

(1) When randomly selecting businesses in a strata, the businesses shall be

weighted so that larger businesses have a greater chance of being sampled, proportionate to the size of the business.

(d) In addition to composition data collected by sorting waste samples, the jurisdiction

shall collect information on generators and strata characterized. This data is needed to extrapolate sample data as specified in Section 18726.54. This information consists of the following:

(1) An estimate of the total annual amount of waste disposed by each generator

sampled. Estimates may be obtained from the generator, from the hauler which serves the generator, or the estimate may be made based on the size of waste container used by the generator and the frequency of collection of waste from the container.

(2) Number of employees or residents at each generator site sampled.

(3) Total number of employees or residents in each strata sampled.

(4) Total number of employees or residents in the subpopulation or sector being

characterized. (e) When only a portion of the waste in a generator’s garbage bin is needed to meet

minimum sample weight or volume, that portion shall be chosen randomly and the bin shall be divided vertically rather than horizontally. For example, waste shall be removed from the right half or left half of the garbage bin rather than the top half or bottom half. This procedure ensures that sample selection addresses settling of heavy objects that may be missed when waste is only removed from the top portion of a bin.

(f) If for a particular targeted study, or in a particular jurisdiction, stratification of

generators is not possible or desirable for the study purposes, another sampling design may be used only if approved by Board staff prior to the beginning of the study. A description of the alternative method shall be submitted to the Board for review and approval. Within 10 working days from receipt of this material, Board staff shall inform the applicant if the application is deficient, and what specific additional information is required. Board staff shall approve or disapprove of the alternative


method within 30 days from the date the jurisdiction submits sufficient information. The jurisdiction may appeal Board staff's disapproval of the alternative method to the Board. The alternative plan and Board approval shall be included in the Waste Characterization Component of the revised SRRE.

NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.54 Data Analysis for Generator Sampling (a) The extrapolation formulas below shall be used for generator studies for the non-

residential sector, to address the variability between businesses. These formulas use the information described in Section 18726.52(d). The purpose of data extrapolation is to use information from individual samples to estimate the overall composition of the waste stream that was sampled. Jurisdictions may calculate the formulas by hand, use a self-developed electronic spreadsheet, or use an electronic spreadsheet provided by the Board. The statistical method used is called "a ratio estimator using stratification with probability proportionate to size."

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(b) The jurisdiction may use another data analysis procedure if it demonstrates that it is

a more appropriate method for analyzing the specific data collected, and if approved by Board staff on a case-by-case basis, as described in Section 18726.52(f) of this Article.


(c) To improve accuracy, the variability between businesses sampled shall be taken into

account in the extrapolation. This is done by weighting the sample data from individual businesses so that the composition data from the larger companies is given more weight. This will result in a composition that better reflects the whole group of businesses. The general extrapolation approach is as follows:

(1) First an individual "disposal correlative factor" of tons disposed per employee

per year is calculated, for each business sampled. A disposal correlative factor relates the amount of waste disposed to the number of employees at the business. When the businesses have been grouped into strata, as described in Section 18726.52 of this Article, an average disposal correlative

factor for each stratum can be developed. This takes the variability due to

business size into account. The overall disposal correlative factor for the subpopulation is the weighted average of the strata disposal correlative factors.

(2) Data from each stratum is used to develop the overall composition for the

subpopulation. It is more accurate to give the composition of a larger stratum more weight than a smaller one, rather than simply averaging the two compositions. This is done by weighting the composition of each stratum by the number of employees in that stratum. This addresses the variability in a subpopulation due to strata being different sizes. For example, the composition of one stratum with 9,000 employees is given more weight than the composition of a second stratum which has only 1,000 employees.

(d) If the jurisdiction cannot obtain all the data required for the formulas, the formulas

may be modified to use the data that is available. The general approach of weighting individual sample data shall be followed in the modified formula.

(e) For residential generator sampling studies, the average composition of each

subpopulation shall be determined according to the procedure in Section 18726.45 of this Article. To determine the composition of the residential sector, the weighted average composition of the subpopulations shall be used.

(f) If generator sampling is used to determine an overall composition for the non-

residential sector, the composition of each subpopulation in the sector shall be weighted according to the tonnage contributed by the subpopulation to the sector's overall tonnage amount.

(g) If generator sampling data is used to determine the tonnage disposed by a sector,

the accuracy of the sector tonnage amount may be checked against information from the disposal reporting system. Information from the disposal reporting may be used to adjust data from the DC study to improve accuracy.

(h) If generators were not stratified, and were randomly chosen, average compositions

shall be determined as in Section 18726.45.


NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.60 Use of Alternatives to the Minimum Requirements for Landfill

and Generator Sampling (a) A jurisdiction may conduct sampling in only one season if it meets all of the following

requirements: (1) it has determined that sampling during only one period during the year will

provide data that is statistically representative and reflects seasonal variation in the waste stream being characterized;

(2) it receives approval from Board staff for the alternative sampling plan prior to

the beginning of the DC study, as described in Section 18726.52(f) of this Article; and

(3) the DC study characterizes the minimum number of samples as specified in

Sections 18726.40 and 18726.50 of this Article. (b) A jurisdiction may use minimum sample numbers lower than those specified in

Sections 18726.40(a) and 18726.50(b) of this Article if it meets one of the following two requirements, and it receives approval by Board staff for the alternative sampling plan prior to the beginning of the DC study, as described in Section 18726.52(f) of this Article.

(1) it demonstrates that the proposed alternative sampling plan will provide data

that is statistically representative for the purpose of the DC study (for example, a DC study focused on 20 specific businesses);

(2) it demonstrates only limited sampling is possible due to financial or other

resource constraints. NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code. Section 18726.70 Combining Data Collection Approaches DC studies conducted using a combination of data collection approaches will be considered statistically representative if data collected from each approach is shown to be statistically representative according to the above requirements. NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code.


Section 18726.90 Reporting Requirements (a) Jurisdictions shall report information on how the DC study was designed and

conducted, and information on the results of the study, as specified in this Article. Any conditions set by the Board for DC studies shall be included. The results of consideration of the factors listed in Section 18726.2 and how determination of the data collection approach shall be discussed in the Waste Characterization Component of the revised SRRE.

(b) The following information shall be reported for sampling studies:

(1) number of samples in each sector or subpopulation sampled (2) stratification procedure, if one was used (3) timing of sampling, number of samples in each season, and how seasons

were identified (4) sample selection procedure (5) whether samples were physically or visually sorted (6) sample weights or volumes (may be reported as range) (7) conversion factors used to convert volume to weight (8) composition of each sector, subpopulation, or group characterized, including

percent composition of each material type, confidence interval for each material type at the 90% confidence level, and estimated tonnage or cubic yards of each material type. The minimum level of reporting shall be the sector level.

(9) For non-residential generator sampling, the number of strata used, number of samples taken in each strata, and average disposal correlative factor for each strata shall also be reported.

(c) Table 3 is an example of how data may be reported to the Board for sampling

studies.


Table 3. Example Format for Data Reporting. Residential Sector Waste Composition

Material Type Average Composition

(%)

± Confidence Interval at 90%

Confidence Level

Estimated Tonnage for

Waste Stream

Paper 31 5 310 Glass 12 4 120 Metal 7 3 70 Plastic 8 2 80 Other Organic 34 6 340 Construct./Demo. 6 3 60 Household Hazard. 1 1 10 Special Waste 1 1 10 Seasons Identified, Timing of Sampling: 2, Winter & Summer

Number of Samples per Season: 15

Total Number of Samples: 30

Estimated total tonnage of Residential Waste Stream: 1,000 tons

(d) For studies conducted using default data or existing data, the composition

percentage of each material type or subtype and estimated tonnage shall be reported. The minimum level of reporting shall be the sector level.

(e) The following information shall also be included in the Waste Characterization

Component of a revised SRRE:

(1) Any Board-approved revision to base year generation, disposal, or diversion amounts

(2) Residential and non-residential percentage of the waste stream, and amount

of waste disposed by the jurisdiction, as reported in the most current Annual Report

(3) Revised or updated solid waste projections which list the total tonnages of

disposal, diversion, and generation, and the percentage of solid waste diverted, for at least 10 years following the year the revised SRRE is submitted to the Board. Projections shall be developed according to Section 18722.10 of Article 5.0 of this Chapter, except that projections may be developed starting with the year the revised SRRE is submitted to the Board rather than the base year.

(f) If discrepancies are found between disposal reporting information collected

according to Article 9.0 of this Chapter and data collected for a DC study, these discrepancies shall be discussed in the Waste Characterization Component of the revised SRRE.



NOTE: Authority: Section 40502 of the Public Resources Code. Reference: Sections 41770, 41030, 41032, 41033, 41330, 41332, and 41333 of the Public Resources Code.

C.2 GUIDELINES GOVERNING HEALTH AND SAFETY MEASURES

DRAFT HEALTH AND SAFETY PROTOCOL Original: Yes Replaces: None Date: April 7, 1995

ARTICLE 6.0 DISPOSAL CHARACTERIZATION STUDIES

Health and Safety Guidelines for Waste Characterization Studies

1. Introduction: The purpose of this document is to provide safety guidelines for performing visual and/or physical characterizations of non-hazardous solid waste from various selected garbage dumpsters, transfer stations, and sanitary landfills. 2. Table of Contents: 1.0 Introduction 2.0 Table of Contents 3.0 Specific procedure 3.01 List of Potential Hazards 3.02 Recommended Personal Safety/Protective Equipment 3.03 Responsible Personnel 3.04 General Safety Procedures 3.05 Site Control in Work Zones 3.06 Site Resources and personnel 3.07 Site Maps 3.08 Agreement to Comply with the Health and Safety Plan 3. Specific Procedure:

3.01 List of potential hazards

The following section lists some possible hazards that may occur during a visual and a physical sort of solid waste.

a. Physical hazards:

Cuts and punctures from handling hazardous materials:

hypodermic needles, broken glass, razor blades, aerosol cans, chemicals, biohazards, bottles of unknown/unlabeled substances, plastic bottles containing used syringes, and other hazardous materials

Back injury Slipping and falling Heat stress and fatigue


Traffic or heavy equipment movement Noise exposure from operation of heavy equipment Animal and/or insect bites

b. Airborne contaminants:

Dust from solid waste

c. Chemical hazards:

Liquid spills from containers Household and hazardous chemicals

d. Biological hazards:

Household hazardous wastes Medical wastes and sharps Bloody rags or objects Hypodermic needles

3.02 Recommended personal safety/protective equipment

The following section lists some of the personal safety/protective equipment

recommended for a visual and physical sort of solid waste.

a. Body protection:

Tyvek or equivalent, disposable coveralls Chemical resistant coveralls, if appropriate Hard bottomed, non-slip, steel toe boots A supply of outer rubber (cut and puncture resistant) gloves Chemical goggles or safety glasses with splash shields Dust masks A supply of inner (latex) gloves Snake guards, if appropriate Insect repellent Dog repellent

b. Hearing protection (if site has equipment or activities that generate loud noises):

Ear plugs Ear muffs

c. Other safety equipment:

Supportive back belt for heavy lifting


Industrial first aid kit Field blanket Eye wash kit Moist, disposable towelettes (e.g., baby wipes) Six foot pole Small fire extinguisher Portable telephone High visibility traffic cones and tapes Site specific safety plan Liquids to replenish fluids (water and cups for dehydration)

3.03 Responsible personnel

The following section lists some of the duties and responsibilities of personnel

who are supervising and conducting a visual/physical sort of solid waste.

a. Supervising, Project Manager's duties and responsibilities:

Delegate health and safety responsibilities to the Site Safety Officer, ensure that proper procedures are implemented by qualified personnel in a safe manner, make available proper personal protective equipment, adequate time, and budget.

Ensure that all field personnel have read, understood, and

signed the master copy of this document.

Check that all the site personnel have received, and documented training on waste characterization methods, recognizing hazardous wastes, potential risks from handling hazardous materials, managing site traffic, controlling dust/airborne contaminants, and back injury prevention.

b. Site Safety Officer's (can be the same person as above) duties and

responsibilities:

Has the duty and authority to stop unsafe operations, supervise CPR, and decide when to summon emergency services.

Ensure that the guidelines, rules, and procedures in this

document are followed for all site work.

Be familiar with local emergency services, and maintain a list of emergency phone numbers. Provide a map with the quickest route to a medical facility.

Conduct daily tailgate health and safety meetings before each

shift, and a daily summary meeting at the end of each shift to


discuss the day's safety issues, possible solutions, and notify personnel of all changes associated with health, safety, and protocol.

Maintain and inspect personal protective equipment. Ensure

proper use of personal protective equipment by all employees.

Monitor on site hazards and the early health warning signs (e.g., heat stress/stroke, dehydration, or fatigue) of site personnel. It is recommended that on hot days, outdoor sampling should be done during the early hours.

Has completed appropriate health and safety training.

(Recommended: 40-hour Hazardous Waste Operation & Emergency response, CCR, T8, Section 5192-OSHA).

3.04 General safety procedures

The following section lists some of the general safety procedures

recommended for a visual/physical sort of solid waste.

a. All waste sorting personnel should: be in good physical condition, have had a recent medical exam, maintain a current tetanus booster and Hepatitis B shot, not be sensitive to odors and dust, and be able to read warning signs/labels on waste containers.

b. There will be absolutely no eating, smoking or drinking during sorting

activities. Food and liquids are to be away from the sorting area. Plenty of fluids (e.g., water, sports drinks, etc.) and single use, disposable cups must be available at all times. Hands and faces should be washed before eating or drinking. Consume drinks and rest frequently during hot days.

c. The "line of sight buddy system" must always be maintained at the

sorting site. The "line of sight buddy system" is as follows: sorters are grouped into pairs and each member is to periodically assess the physical condition of his/her "buddy".

d. Always wear the following before beginning the sorting procedure:

both pairs of gloves (outer rubber and inner latex), chemical goggles or safety glasses with splash shields, a dust mask, and disposable Tyvek overalls. Use safety boots especially when getting into bins.

e. Make noise when approaching the actual waste site to allow any

wildlife/pest animals to flee. Look for snakes and poisonous spiders around and inside a dumpster/bin by probing with a long stick.


f. Do not attempt to identify unknown chemical substances present in the waste stream: vials of chemicals, unlabeled pesticide/herbicide containers, and substances (e.g., chemicals, or needles) in unlabeled plastic/glass bottles/jugs.

g. Household hazardous wastes are those wastes resulting from

products purchased by the public for household use which because of their quantity, concentration, physical, or infectious, characteristics, may pose a substantial known or potential hazard to human or environmental health when improperly disposed. Empty containers of household hazardous wastes are generally not considered to be a hazardous waste. If hazardous wastes are detected, the Site Safety Officer will be notified.

h. Hazardous materials and hazardous wastes should not be present in

non-residential sources of municipal solid waste. If hazardous wastes are present in the municipal waste stream, from a commercial or industrial source, the material is not a household hazardous waste, it is a hazardous waste and the Site Safety Officer must be notified.

i. Biohazardous wastes are generally disposed of in red, plastic bags.

Treated biohazardous wastes (by incineration, autoclave, chemical sterilization, etc.), are also usually in red bags. If biohazardous wastes are detected, the sort will be halted (the bag will not be removed from the dumpster/bin) and the Site Safety Officer must be notified.

j. A potential hazard that can arise in waste sampling is the presence of

biohazardous wastes that are not in red bags, referred to as "fugitive regulated wastes". Sorters must be on alert for the indicators of fugitive biohazardous wastes: hypodermic needles, needle covers, medical tubing, articles contaminated with red (blood) colored substances, and medical device packaging. If fugitive biohazardous wastes are detected, the sort will be halted and the Site Safety Officer notified.

k. When sorting glass, remove the large pieces first, then remove the

clear glass. Never use your hands to dig down through the waste. Use a rake or small shovel to pull/push the material to the side and continue sorting.

l. At the end of each shift, remove all disposable clothing into a plastic

trash bag, and place the bag into a solid waste receptacle. All sorters must shower at the end of each shift.

3.05 Site control in work zones

The following section lists site control recommendations for a visual/physical

sort of solid waste.


a. Traffic cones or high visibility warning tape will be placed around the

active sorting area.

b. Each work crew will keep a site specific safety plan on site at all times.

3.06 Site resources and personnel

The following section lists available site contacts and resources for a

visual/physical sort of solid waste.



a. On-site contact:

Main point of contact: Telephone number: Facility manager: Telephone number:

b. Site resources locations

Toilet facilities: Drinking water: Telephone:

c. Medical information:

Local emergency medical facility: Fire Dept. phone number: Police Dept. phone number: Local ambulance phone number:

3.07 Site maps

See attachments for a site map that shows the location of local medical

facilities.

3.08 Agreement to comply with the health and safety plan

I _______________________________________ have read and understand print name the health and safety plan and will follow the procedures and protocols

detailed in the plan for waste characterization at all designated sites.

C.3 GUIDELINES GOVERNING SOLID WASTE SORTING PROCEDURES

DRAFT PHYSICAL AND VISUAL SORTING PROTOCOL Original: Yes Replaces: None Date: April 7, 1995

ARTICLE 6.0 DISPOSAL CHARACTERIZATION STUDIES

Physical and Visual Solid Waste Sorting Procedures 1. Introduction: The purpose of this document is to provide guidelines for performing visual and/or

physical sorts of non-hazardous solid waste from selected garbage dumpsters, transfer stations, and sanitary landfills.

2. Table of Contents: 1.0 Introduction 2.0 Table of Contents 3.0 Specific procedure

3.01 Recommended Personal Safety/Protective Equipment 3.02 Recommended Sorting Equipment 3.03 General Sorting Protocol 3.04 Physical, Non-hazardous Solid Waste Characterization 3.05 Visual, Non-hazardous Solid Waste Characterization

3. Specific Procedure:

3.01 Recommended personal safety/protective equipment Please see The Health and Safety Plan for Waste Characterization Studies

document, page 2, section 3.02. 3.02 Recommended sorting equipment

a. Knife with a fixed blade. b. Small bins or buckets (5 gal and/or larger) for weighing sorted

materials. c. Sorting table. d. A scale that is accurate to one-tenth of a pound. Depending upon the

waste stream, a larger capacity scale may be useful. e. Tongs. f. Permanent markers. g. Clipboard and data sheets. h. Large magnets. i. Calculator.


j. Trash bags. k. Step ladder. l. A long stick, approximately 6' in length. m. Rake with a long handle. n. Rake with a short handle. o. Shovel with a long handle. p. Broom q. Camera & film r. Duct tape s. Plastic sheeting (minimum of 10 mm thick)

3.03 General sorting protocol

a. If physical sampling is to be performed at the business site of a generator, try to minimize interference with normal operations.

b. Place traffic cones or high visibility warning tape around the active

sorting area. c. Make noise when approaching the actual waste site to allow any

insects/pest animals to flee. Look for snakes, bees, wasps, and poisonous spiders around and inside a dumpster/bin by probing with a long stick.

d. Always wear the following before beginning the sorting procedure:

both pairs of gloves (outer rubber and inner latex), chemical goggles or safety glasses with splash shields, a dust mask, and disposable Tyvek overalls.

e. There will be absolutely no eating, smoking or drinking during sorting

activities in the sorting area. Plenty of fluids (e.g., water, sports drinks, etc.) must be available away from the sorting area. Hands and faces should be washed before eating or drinking. Frequent rest, drink and food breaks should be given during hot days.

f. Do not attempt to identify unknown chemical substances present in

the waste stream: vials of chemicals, unlabeled pesticide/herbicide containers, and substances (e.g., chemicals, or needles) in unlabeled plastic/glass bottles/jugs.

3.04 Physical, non-hazardous solid waste characterization

a. The "line of sight buddy system" must always be maintained at the sorting site. The "line of sight buddy system" is as follows: sorters are grouped into pairs and each member is to periodically assess the physical condition of his/her "buddy".


b. Set up the sorting table. It is recommended that the labeled buckets be placed around the table so that the buckets that will receive the most material are nearest to the table. To reduce reaching distances, all buckets within a broad material category (i.e. paper) should be positioned close together.

c. Place plastic sheeting or tarp over the surface where the solid waste

is to be sorted. Tape the edges of the cover down with duct tape or weight it down. The cover will protect the surface from stains.

d. When removing only part of the contents of a dumpster/bin, use a

shovel (and a ladder, if needed) to remove the sample all the way to the bottom to insure that smaller, more dense elements are included. Remove subsamples of approximately 50 pounds (estimate: normally 100 pounds per cubic yard) from a preselected dumpster/bin onto the table until an appropriate sample weight has been sorted. If there is not enough material in a dumpster/bin, sort the entire contents. It is recommended that sampling occur when the dumpsters/bins are at their fullest, right before pick up.

e. Tear open garbage bags (not red bags) with rakes or other equipment

and visually inspect for potential hazards. If hazardous or biohazardous wastes are detected, the sort will be halted and the Site Safety Officer must be notified.

f. Begin the sort by removing and characterizing the largest, bulkiest

elements. Sort the remaining items into the categories and material types shown on the sample sheet. If a bucket becomes full, the full bucket is weighed, the data recorded on the data sheet, and the bucket is emptied and reused. Weigh and record the total mass (contents + bucket) on the data sheet. Record the type of bucket used so that later, the mass of the buckets can be subtracted from the total weight.

g. When sorting glass, remove and sort the larger pieces that are on top

first. Never use your hands to dig down through the waste. Use a rake or small shovel to pull/push the material to the side and continue sorting.

h. When a sorter has a question regarding the material category or type

into which an element should be placed, the Crew Leader will be consulted. For composites or multi material items, the predominate material type (as measured by weight) determines which material type it belongs.

i. Return all sorted materials to their dumpster/bin.


j. At the end of each shift, remove all disposable clothing into a plastic trash bag, and place the bag into a solid waste receptacle. Reusable equipment cleaned and sanitized after use. All sorters must shower at the end of each shift.

3.05 Visual, non-hazardous solid waste characterization

a. For the following wastes; a visual (not a physical sort) is appropriate: wastes that contain large quantities of bulky or heavy items (e.g., concrete demolition material), consist of materials too small to be sorted (e.g., ash), consist of materials that may be too dangerous to sort (e.g., chemical or biohazards), or are of primarily one type of material.

b. Photographs can be taken to document waste types or, used when

other constraints (such as odor or business hours) sharply limit field sampling time. A 35mm camera using either fine-grained, professional color print film (e.g., Royal Gold); professional grade Kodachrome slide film or; an equivalent film type will be sufficient. Prints should be a minimum of 8" by 10". Photographs or slides should be taken from as close to a vertical position as possible above the spread-out sample. Mark out a rectangle on the image in which the waste types are to be identified. Some have found that subdividing the rectangle helps with keeping track of the sample areas and in identifying components.

c. For "in bin" visual characterizations, solid waste in dumpsters/bins can

be visually inspected by personnel standing outside the dumpster/bin on a step ladder. Do not remove bags/material from the dumpster or bin. Use a rake or other equipment to break open bags and expose materials for visual characterization.

d. A recommended minimum of 2 persons shall conduct each sort, one

person to characterize the solid waste, the other to record data. Independent observations and estimates of the volumes of the various waste materials should be attempted.

e. The average of the volume estimates should be used along with a

density conversion table to convert the volume data to weight percentage. The sum of the average volumes should total 100% so, some adjustment in the 100% volume may be necessary. For materials with no published density conversion data, a sample can be weighed and volume measured to develop a conversion factor. Refer to section 4.04 above for physical sort guidelines.

f. Unidentifiable materials can be put into the "miscellaneous/unsorted"

category. The rules for composites and multi-material waste characterization should be followed. For composites or multi-material



items, the predominate material type as measured by weight determines which material type it gets classified as. When a sorter has a question regarding the material category or type into which an item should be placed, the Crew Leader should be consulted.

g. For visual characterizations that are removed from the bin, ensure

that smaller, denser items are included in the sort by sampling all the way to the bottom of the dumpster/bin. Do not sort only the top layers and consider the sampling procedure completed.

h. A load that is to be visually characterized should be spread into a thin

layer (approx. 6-8 inches) so that nothing is covered by other objects. Periodically rake through the layer to determine if there are hidden waste types. If the lower layers are significantly different, remix them.

APPENDIX D: FORMS USED IN THE STUDY

FORM USED FOR VEHICLE SURVEYS Date _____________ Page _____ of _____Survey Site __________________________Survey Site __________________________ Surveyor Minimum weight at this site ______________ Checked by Data Entry #1 _____

Data Entry #2 _____As All Vehicles Approach For Self-Haul Loads Only Surveyor's

NOTESVehicle License or ID

Number Substream Net Weight of LoadActivity that Generated

Self-Haul WasteRSF residential single family

SH self-haul Ask driver to estimate % of load RMF residential multi-familySF single family residential that is SF, MF and Com that is SF, MF and Com Indicate whether units are C&D construction & demolitionMF multi-family residential tons, pounds, RF roofingC commercial or cubic yards L landscapingIf "mixed", then fill out O other commercial, ind-percentages. % SF % MF % Com (circle units) ustrial or institutional

1 SH SF MF C tons lbs yds RSF RMF C&D RF L O















1. Make entries neatly in pen.2. Enter the information at the top of each page. Enter total # of pages on each page at the end of the day.3. Enter the vehicle license or ID number, if you need it to get vehicle net weights. It is not needed otherwise for the survey.4. In the Substream column, circle either SH or one/more of the other three. If you circle SH, go to Self-haul Load Only.5. If you do not circle SH, circle some combination of SF, MF, or C. Ask the driver what categories of waste are in the vehicle.6. If you circle more than one of the SF, MF or C entries, be sure to ask the driver for the % of each.

7. Enter the weight. If the operator measures self-haul loads by volume, record the volume and indicate that the unit is "yds".8. If the load is self-haul, circle only one of the entries in the For Self-Haul Only column. If you circle O, write a note saying what type of business the load is from.9. If you make an error on an entry, draw a line through the entire entry and start over on a new line.

For mixed MF and SF res & com (X)

Must total 100%

California 1999 Statewide D - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board


SNAPSHOT OF GENERATOR RECRUITMENT DATABASE

SNAPSHOTS OF DATABASE FOR ENTRY OF COMPONENT WEIGHTS IN THE FIELD ENTRY FOR DISPOSAL SITE SAMPLE

California 1999 Statewide Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

D - 3


ENTRY FOR GENERATOR SAMPLE

APPENDIX E: DEFINITIONS OF BUSINESS GROUPS

Table 78: Description of Industry Groups Designated in the Study

Assigned Code

Description of Group

SIC Codes Included

SIC Code Designations

A Finance / Insurance / Real Estate / Legal 60 Depository institutions 61 Nondepository credit institutions 62 Security, commodity brokers, and services 63 Insurance carriers 64 Insurance agents, brokers, and service 65 Real estate 67 Holding and other investment offices 81 Legal services

B Retail Trade - Restaurants 58 Eating and drinking places C Retail Trade - Other 56 Apparel and accessory stores 57 Furniture, home furnishings and equipment stores 59 Miscellaneous retail

D Services - Other Misc. 72 Personal services 75 Automotive repair, services, and parking 76 Miscellaneous repair services 79 Amusement and recreational services 83 Social services 84 Museums, art galleries, botanical & zoological garden

E Wholesale Trade - Nondurable Goods 51 Wholesale trade--nondurable goods F Retail Trade - Automotive Dealers & Service Stations 55 Automotive dealers and gasoline service stations G Services - Other Professional 86 Membership organizations 87 Engineering and management services 89 Miscellaneous services

H Retail Trade - Food Store 54 Food stores

California 1999 Statewide E - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

Assigned

Code Description of Group

SIC Codes Included


I Construction 15 General building contractors 16 Heavy construction contractors 17 Special trade contractors J Services - Medical / Health 80 Health services K Manufacturing - Printing / Publishing 27 Printing and publishing L Services - Business Services 73 Business services M Services - Education 82 Educational services N Public Administration 43 U.S. Postal Service 91 Executive, legislative, and general government 92 Justice, public order, and safety 93 Finance, taxation, and monetary policy 94 Administration of human resources 95 Environmental quality and housing 96 Administration of economic programs 97 National security and international affairs

O Services - Hotels / Lodging 70 Hotels, rooming houses, camps, and other lodging places P Trucking & Warehousing 42 Motor freight transportation and warehousing Q Wholesale Trade - Durable Goods 50 Wholesale trade--durable goods R Manufacturing - Other 21 Tobacco manufactures 29 Petroleum and coal products 30 Rubber and miscellaneous plastics products 31 Leather and leather products 32 Stone, clay, glass, and concrete products 39 Miscellaneous manufacturing industries

S Transportation - Other 40 Railroad operation 41 Local and interurban passenger transit 44 Water transportation 46 Pipelines, except natural gas 47 Transportation services


Assigned

Code Description of Group

SIC Codes Included


T Manufacturing - Electronic Equipment 36 Electrical and electronic equipment U Manufacturing - Food / Kindred 20 Food and kindred products V Manufacturing - Lumber & Wood Products 24 Lumber and wood products W Manufacturing - Transportation Equipment 37 Transportation equipment X Retail Trade - Building Material & Garden 52 Building materials, hardware, garden supply, & mobile Y Manufacturing - Industrial / Machinery 35 Industrial machinery and equipment Z Agriculture / Fisheries 01 Agricultural production- crops 02 Agricultural production- livestock 07 Agricultural services 09 Fishing, hunting, and trapping

AA Manufacturing - Instruments / Related 38 Instruments and related products AB Communications 48 Communications AC Manufacturing - Primary / Fabricated Metal 33 Primary metal industries

34 Fabricated metal products AD Manufacturing - Apparel / Textile 22 Textile mill products

23 Apparel and other textile products AE Manufacturing - Furniture / Fixtures 25 Furniture and fixtures AF Services - Motion Pictures 78 Motion pictures AG Manufacturing - Chemical / Allied 28 Chemicals and allied products AH Retail Trade - General Merchandise Store 53 General merchandise stores AI Mining 10 Metal mining 12 Coal mining 13 Oil and gas extraction 14 Nonmetallic minerals, except fuels

AJ Transportation - Air 45 Transportation by air AK Utilities 49 Electric, gas, and sanitary services AL Manufacturing - Paper / Allied 26 Paper and allied products AM Forestry 08 Forestry


APPENDIX F: DISTRIBUTION OF EMPLOYMENT BY BUSINESS

GROUP AND REGION

Table 79: Numbers of Employees by Industry Group in Each Region

Region Industry Group Coastal Bay Area Southern Mountain Central Totals A - Finance / Insurance / Real Estate / Legal 42,004 310,193 711,016 16,421 128,730 1,208,364 B - Retail Trade - Restaurants 38,299 179,248 510,685 18,292 106,972 853,496 C - Retail Trade - Other 33,797 231,180 469,780 14,346 86,925 836,028 D - Services - Other Misc. 51,940 235,230 620,366 24,845 137,652 1,070,033 E - Wholesale Trade - Nondurable Goods 29,635 64,555 234,844 3,720 78,163 410,917 F - Retail Trade - Automotive Dealers & Service Stations 10,909 48,995 172,776 7,061 40,804 280,545 G - Services - Other Professional 26,574 177,787 371,562 12,793 74,658 663,374 H - Retail Trade - Food Store 18,290 71,019 204,221 9,386 48,581 351,497 I - Construction 21,286 112,779 249,629 13,048 61,726 458,468 J - Services - Medical / Health 49,319 305,611 764,759 25,185 205,000 1,349,874 K - Manufacturing - Printing / Publishing 5,557 54,610 130,115 2,634 18,229 211,145 L - Services - Business Services 18,583 185,019 343,841 6,240 57,399 611,082 M - Services - Education 40,259 173,851 534,793 20,349 150,371 919,623 N - Public Administration 24,871 133,872 375,728 20,500 104,954 659,925 O - Services - Hotels / Lodging 13,285 45,106 128,983 18,440 17,389 223,203 P - Trucking & Warehousing 5,179 25,284 72,257 2,356 26,271 131,347 Q - Wholesale Trade - Durable Goods 16,018 151,178 387,437 5,953 56,539 617,125 R - Manufacturing - Other 3,696 23,270 124,081 1,143 15,546 167,736 S - Transportation - Other 4,474 39,688 97,504 3,606 15,874 161,146 T - Manufacturing - Electronic Equipment 5,016 114,637 134,671 775 11,298 266,397 U - Manufacturing - Food / Kindred 12,545 24,009 53,734 832 61,680 152,800 V - Manufacturing - Lumber & Wood Products 6,152 2,268 11,975 4,459 9,485 34,339 W - Manufacturing - Transportation Equipment 969 21,928 111,446 222 3,399 137,964 X - Retail Trade - Building Material & Garden 7,375 26,331 72,132 4,357 24,052 134,247 Y - Manufacturing - Industrial / Machinery 5,874 89,741 108,937 1,195 15,929 221,676 Z - AM Lumped Group 35,268 244,220 777,818 17,397 146,297 1,221,000Totals 527,174 3,091,609 7,775,090 255,555 1,703,923 13,353,351

Data was obtained from Dun and Bradstreet in October 1999.

California 1999 Statewide F - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

California 1999 Statewide F - 2 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

Table 80: Numbers of Businesses by Industry Group in Each Region

Region Industry Group Coastal Bay Area Southern Mountain Central Totals A - Finance / Insurance / Real Estate / Legal 7,113 40,426 96,931 3,837 21,031 169,338 B - Retail Trade - Restaurants 2,865 13,693 35,253 1,698 7,612 61,121 C - Retail Trade - Other 6,679 27,295 78,326 3,573 13,889 129,762 D - Services - Other Misc. 9,587 38,836 100,856 5,293 23,341 177,913 E - Wholesale Trade - Nondurable Goods 1,625 4,678 16,333 578 3,252 26,466 F - Retail Trade - Automotive Dealers & Service Stations 1,309 4,411 16,160 812 4,169 26,861 G - Services - Other Professional 4,972 23,006 50,383 2,605 12,117 93,083 H - Retail Trade - Food Store 1,451 5,840 16,463 853 4,249 28,856 I - Construction 4,320 13,481 35,932 3,452 9,486 66,671 J - Services - Medical / Health 5,221 25,204 63,321 2,414 13,454 109,614 K - Manufacturing - Printing / Publishing 621 3,734 9,474 297 1,374 15,500 L - Services - Business Services 3,118 17,158 39,460 1,644 7,019 68,399 M - Services - Education 1,173 4,709 11,771 812 3,404 21,869 N - Public Administration 1,826 4,237 10,214 2,060 4,650 22,987 O - Services - Hotels / Lodging 1,004 1,496 4,716 1,120 1,100 9,436 P - Trucking & Warehousing 576 1,873 5,495 445 1,960 10,349 Q - Wholesale Trade - Durable Goods 1,910 12,789 37,554 1,079 6,054 59,386 R - Manufacturing - Other 353 1,604 5,777 196 845 8,775 S - Transportation - Other 566 3,778 9,008 381 1,352 15,085 T - Manufacturing - Electronic Equipment 101 1,563 2,598 38 177 4,477 U - Manufacturing - Food / Kindred 399 717 985 89 504 2,694 V - Manufacturing - Lumber & Wood Products 180 166 493 201 229 1,269 W - Manufacturing - Transportation Equipment 54 184 1,073 26 137 1,474 X - Retail Trade - Building Material & Garden 922 2,319 7,084 675 2,191 13,191 Y - Manufacturing - Industrial / Machinery 241 2,150 6,270 181 716 9,558 Z - AM Lumped Group 2,719 9,377 33,489 1,677 7,359 54,621 Totals 60,905 264,724 695,419 36,036 151,671 1,208,755

Data was obtained from Dun and Bradstreet in October 1999.

APPENDIX G: NUMBERS OF SAMPLES BY

SECTOR, SITE, REGION, AND SEASON

DISPOSAL SITE SAMPLES

Disposal-site sampling included samples from the single-family residential, commercial self-haul, and residential self-haul sectors. The tables below present the numbers of disposal site samples that were captured and sorted in each region, during each season, and at each site. (Please refer to Table 71 for the proper name and location of each disposal site listed below.)

Region Coastal Season Winter Summer Totals

Disposal Site Monterey Regional

Central Landfill

Buena Vista John Smith Johnson Canyon

Single-Family Residential 6 6 5 6 6 29 Commercial Self-Haul 10 7 7 6 6 36 Residential Self-Haul 0 3 3 4 4 14 Totals 16 16 15 16 16 79

Region Bay Area Season Winter Summer Totals

Disposal Site South Bayside

Ox Mountain Davis Street Potrero Hills Berkeley T.S.


Region Southern Season Winter Summer Totals

Disposal Site Bradley Landfill

Sunset Environmental

Victorville Refuse

Universal Refuse

Falcon Refuse


California 1999 Statewide G - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

Region Mountain Season Winter Summer Totals

Disposal Site City of Redding

West Central L.F.

McCourtney Road

South Tahoe Refuse

Western Amador


Region Central Season Winter Summer Totals

Disposal Site Fairmead Auburn Placer

Yolo County Billy Wright American Avenue


GENERATOR SAMPLES

Generator sampling included samples from the commercial and multifamily residential sectors. The tables below present the numbers of generator samples that were captured and sorted in each region, during each season, and in each waste shed. (Please refer to Table 71 for the location of each waste shed listed below.)

Region Coastal Season Winter Summer Totals

Waste Shed Central Landfill

Johnson Canyon

Commercial 37 36 73 Multi-Family Residential 1 2 3 Totals 38 38 76

Region Bay Area Season Winter Summer Totals

Waste Shed South Bayside Kirby Canyon Davis Street Kirby Canyon Commercial 72 52 67 78 269 Multi-Family Residential 3 5 13 3 24 Totals 75 57 80 81 293


Region Southern Season Winter Summer Totals

Waste Shed Bradley Landfill

Victorville Refuse

Bradley Landfill

S.E. Resource Recovery

Commercial 266 24 172 171 633 Multi-Family Residential 21 1 18 4 44 Totals 287 25 190 175 677

Region Mountain Season Winter Summer Totals

Waste Shed City of Redding

South Tahoe Refuse

Commercial 22 36 58 Multi-Family Residential 1 1 2 Totals 23 37 60

Region Central Season Winter Summer Totals

Waste Shed Auburn Placer Billy Wright Commercial 59 115 174 Multi-Family Residential 4 3 7 Totals 63 118 181


APPENDIX H: NUMBERS OF VEHICLES

SURVEYED BY SITE, REGION, AND SEASON

Region Coastal Season Winter Summer Total Disposal Site Monterey

Regional Central Landfill

Buena Vista John Smith Johnson Canyon

Number of Vehicle Surveys 110 152 163 94 24 543 Region Bay Area Season Winter Summer Total Disposal Site South

Bayside Ox Mountain Davis Street Potrero Hills Berkeley

T.S.

Number of Vehicle Surveys 196 128 606 107 132 1,169 Region Southern Season Winter Summer Total Disposal Site Bradley

Landfill Sunset

Environmental Victorville Refuse

Universal Refuse

Falcon Refuse

Number of Vehicle Surveys 519 160 134 16 * 84 913 Region Mountain Season Winter Summer Total Disposal Site City of

Redding West Central

L.F. McCourtney

Road South Tahoe

Refuse Western Amador

Number of Vehicle Surveys 125 52 194 64 52 487 Region Central Season Winter Summer Total Disposal Site Fairmead Auburn

Placer Yolo County Billy Wright American

Avenue

Number of Vehicle Surveys 91 107 137 43 174 552 * The 16 vehicle survey results obtained from Universal Refuse Removal Recycling and Transfer Station were not included in the vehicle survey analysis, because it was determined that the day of surveying did not adequately represent all of the sectors contributing waste to the site.

California 1999 Statewide H - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

APPENDIX I: PAPER ON CALCULATING

RPPC CONTAMINATION RATES

Estimating the Percent of RPPCs in the Waste Stream Report to Cascadia Consulting Group June 7, 1996 Ashley Steel Paul Sampson Department of Statistics University of Washington Problem Overview The goal of these calculations is to produce an estimator of the percent weight of Rigid Plastic Packaging Containers (RPPCs) discarded in California’s landfills and to calculate the variance associated with that estimator. This estimator will eventually be used to calculate the percent of RPPCs that are recycled in California. The percent of RPPCs recycled in California, and the variance of that estimate, will be important tools for assessing how well the legally mandated recycling rate is being met. The abbreviations and subscripts used in the calculation formulas are summarized in the next section of this report along with an outline of the overall strategy for condensing the information into one estimator. Details are provided for each calculation to be carried out. The method explains not only how to calculate the estimator but also how to calculate the variance of the estimator at each step. Data were gathered at 11 waste management centers in August and September of 1995 and at 13 waste management sites in January and February of 1996. These 24 sites were chosen from a list of all landfill and transfer stations in the State of California which met certain minimum requirements; the site must accept all three types of municipal solid waste and it must process a minimum of 100 tons of waste per day. As certain types of waste management facilities were excluded from the selection process, some systematic estimation biases may exist. Although the list of potential waste management sites was randomly ordered, there may also be some selection bias among those sites which agreed to participate in the study. Both types of potential bias and methods for addressing them are discussed in the final section of this report.

California 1999 Statewide I - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

Calculation Strategy The following discussion outlines the steps for going from the data on each component of plastic and its dry versus field weight for three different substreams and 24 different sites, to a final estimate of the overall percent RPPCs going into California’s landfills. The numbers in the discussion refer to the numerical calculations described below each section. The terminology to be used in this discussion and the abbreviations for the calculations are summarized in Table 1.

Table 1: Summary of Terms and Abbreviations

Term Abbreviation Description Waste W The weight of the waste, including both RPPCs and all other

materials. Component C

(c = 1 to 19) The weight of each of the 19 types of RPPC (i.e., PET soda bottles, PS foam).

Field Weight F Weight, as measured at the site. Dry Weight D Weight after being washed and dried. Substream (b = 1 to 3) Each of three types of municipal solid waste: residential,

commercial, self-haul. Site (t = 1 to 24) Each of the 24 transfer stations and landfills. Sample (i = 1 to n) For each site and substream, 6 or 7 samples were taken,

where n = number of samples at a particular cell of interest (for example, self-haul at site #6).

Dry Weight Sub-Sample

(j = 1 to m) For each site and substream, j denotes the number of field samples for which dry weights were calculated.

Note: While substream and site are sampling strata, components are not. Therefore, the subscripts for components, c, will be separated from those of the sampling strata, b, t, and the samples themselves, i, j. Quick Summary of the Steps I) Calculate the ratio of the average field weight to the average total waste weight for each component, in each substream, at each site. II) Calculate the ratio of the average dry weight to the average field weight for each component in each substream at each site. III) Multiply the ratio of field weight to total waste weight by the ratio of dry weight to field weight for each component in each substream at each site.

wasteof weight total

)(component dry weight )(component weight field

)(component dry weight wasteof weight total

)(component weight field=×

IV) Sum the dry weight to total waste weight for all the components within each substream and site. This will give you a ratio of the dry weight for all components to total waste weight for each substream, at each site.


V) Average the ratios of dry weight of all components to total waste weight within each substream across all 24 sites. VI) Take a weighted, by percent of waste in each substream, average of the ratio of the average dry weight of all components to the average total waste weight across all three substreams. This produces one number which is the estimator of the ratio of the dry weight of RPPCs to the total waste weight for all components and across all sites and substreams. Calculations I) Calculate the ratio of the average field weight to the average total waste weight for each component, in each substream, at each site. The first step is to calculate the ratio of the RPPC weight over the weight of total waste for each

component, in each substream, for each site (1). Each of these ratios must be calculated separately so that component-specific adjustments can be made to account for field versus dry weight. Because both the numerator and the denominator of this term are random variables, the approximate variance must be computed using the formula from Cochran (p. 33, 1977) (2). For ease of calculation, in steps (2), (4), and (10), it is probably best to calculate the quantities such as

btcA ,

∑i

btibtic WC )( , and ( )∑i

btiW 2

before you begin the rest of the calculations. (1) btbtcbtc WCA /,, =

where btcC , denotes the average weight of a particular component over all the samples in a particular

substream, b, and at a particular site, t, and btW denotes the average weight of the total sample of

waste over all the samples in that substream, b, and site, t. For example, the average, btcC , , is

calculated as ∑=i

bticbtc Cn

C ,,1 .

(2) ( ) ( ) ( )

222

,,,2

,

, 1

2)(Var

⎟⎟⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜⎜⎜

⎝

⎛

−

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛−

≈∑ ∑∑

∑ n

WAWCAC

WnA i i

btibtci

btibticbtcbtic

ibti

btc

where n is the number of samples in the particular substream and at the particular site for which the statistic is being calculated.


At this point, you should have and the variance of for all 19 components, at all three

substreams and all 24 sites. Therefore, you should have 1,368 values of and a separate variance

for each.

btcA , btcA ,

btcA ,

II) Calculate the ratio of the average dry weight to the average field weight for each component in each substream at each site. Next, the ratio of the dry weight over the field weight, , must be computed for each component,

each substream, and each site (3). Again, this is the ratio of two random variables, and the variance can be computed as in Cochran (4).

btcE ,

(3) btcbtcbtc FDE ,,, /=

where btcD , denotes the average of all m dry weights for a particular substream, b, and a particular

site t, and where btcF , denotes the average field weight of the m samples for which dry weights are

available, at each substream, b, and site, t.

(4)

( ) ( ) ( )2

2,

2,,,,

2,

,, 1

2

)(Var

⎟⎟⎟⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜⎜⎜⎜

⎝

⎛

−

⎟⎟

⎠

⎞

⎜⎜

⎝

⎛+

⎟⎟

⎠

⎞

⎜⎜

⎝

⎛−

≈

∑ ∑∑

∑ m

FEFDED

FmE

j jbtjcbtc

jbtjcbtjcbtcbtjc

jbtjc

btc

where m denotes the number of samples for which dry weights are available in substream b, and at site t. At this point, you should have one field weight to wet weight ratio, , for each component, c, at

each substream, b, for each site, t, and a separate variance for each . btcE ,

btcE , III) Multiply the ratio of field weight to total waste weight by the ratio of dry weight to field weight for each component in each substream, at each site. The next step is to multiply these two ratio estimators together (5) and compute the variance of this product (6). The formulas used in calculating the variance of the product of two independent variables are derived from those in Arnold (1990). In essence, we are making the following calculation for each component, in each substream, and at each site:

wasteof weight total

)(component dry weight )(component weight field

)(component dry weight wasteof weight total

)(component weight field=× .

(5) btcbtcbtc EAG ,,, =


(6) ( ) ( )( ) ( )( ) ( )2,,

2,,

2,,, Var VarVar btcbtcbtcbtcbtcbtcbtc EAEEAAG −++=

IV) Sum the dry weight to total waste weight for all the components within each substream and site. Now that we have an estimate of the ratio of the dry weight of each component to total waste, in each substream, at each site ( ), we can sum over all the components and get an estimate of the

ratio of total RPPC dry weight to the weight of total waste ( ) in each substream and at each site (7). Assuming that within each site and each substream, the estimates of the ratio of the dry component weight to the weight of the total waste are independent, the variance of this estimate is the sum of the variances for the individual components (8).

btcG , btcG ,

btH

(7) ∑=

cbtcbt GH ,

(8) ∑=

cbtcbt GH )(Var)Var( ,

(V) Average the ratios of dry weight of all components to total waste weight within each substream, across all 24 sites. Next, we pool the estimates of the percent RPPCs in each substream across all 24 sites to get one estimate of the ratio of the weight of RPPCs to the weight of total waste for each substream (9). The variance of this estimator, if it is going to be used as an estimate of the substream-specific percentages of RPPCs in all 153 potential sampling sites, must describe both between-site variability and within-site variability. As well, it must include a finite sampling correction (10) (Cochran 1977, Sections 10.2-10.4). In this step, we are assuming that the site-specific estimates of the ratios of RPPCs to total waste in each substream are independent. For further refinements of the variance calculation, please see the attached memo from Paul Sampson to Leina Johansson, May 3, 1996.

)( bN

(9) 24

∑= t

bt

b

HN

(10) ∑∑⎟⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜⎜

⎝

⎛⎟⎠⎞

⎜⎝⎛

+⎟⎟⎠

⎞⎜⎜⎝

⎛−⎟

⎠⎞

⎜⎝⎛

−⎟⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜⎜

⎝

⎛⎟⎠⎞

⎜⎝⎛−

=t

btt

bbtb HNHN )(Var 2415324

)(124

1 24153241

)(Var2

2

Note: The first term of Equation (10) represents the site-to-site variability, and the second term represents the within-site variability. (VI) Take a weighted, by percent waste in each substream, average of the ratio of the average dry weight of all components to the average total waste weight across all three substreams.


The final step is to take a weighted average of the ratio of RPPCs to total weight across the three substreams (13). The variance of this final estimator (O) is the sum of the variance of each of the three estimators times the proportion of waste in that substream squared (14). (13) ∑ ×=

bbb NO ) (prop

(14) ∑ ×=

bbb NO )](Var )prop[()(Var 2

where are the proportions of total waste in each of the three substreams. The variance calculation assumes that the estimates for each substream are independent. Although this assumption may be violated because we have constrained the sum of the three proportions to equal 1, we don’t expect that the estimates would be strongly correlated. If the variances of the estimates within each substream were correlated, one would expect a negative correlation, and so the calculation in step (14) can be considered conservative.

bprop

One should note that for small sample sizes, the distribution of ratio estimators is often asymmetric. Therefore, confidence intervals for ratio estimators based on small sample sizes, for example the ratios of each RPPC component to the total weight in a given substream at a given site, should be calculated using the alternate method proposed in Cochran, p. 156. Because the final estimator here is based on sums of ratio estimators, we can use the central limit theorem and assume that our final distribution is asymptotically normal and standard confidence intervals can be computed. Sampling Bias The two types of potential bias in this sampling design, as described briefly in the introduction, are systematic bias from excluding certain types of waste management facilities from the analysis and selection bias caused by the difficulties in finding site managers who were willing to participate in the study. The best way to assess how much bias might exist is to gather some simple information about the waste management sites which did not participate in the study. Using this information, it would be possible to design some sensitivity analyses which placed boundaries around the final estimator, describing the worst-case scenarios. For example, if 10% of the facilities which were not sampled were small specialty facilities which handled a large percentage of RPPCs, one could calculate a final estimator based on a weighted sum of 0.90 multiplied by Q or Z, the final estimate of RPPCs per total weight of waste in the sites which were sampled and 0.10 times some multiple, for example two or three, of the final estimate. The estimator from these calculations could be presented as an estimate of the final percent of RPPCs in the worst-case situation where the small, unobservable facilities see, for example, two or three times the RPPCs of the Larger, observable facilities.


References Arnold, S. F. 1990. Mathematical Statistics. Prentice-Hall, Inc.: New Jersey. Cochran, W. C. 1977. Sampling Techniques. John Wiley and Sons: New York. Zar, J. H. 1984. Biostatistical Analysis. Prentice-Hall, Inc.: New Jersey.


APPENDIX J: COUNTY DEMOGRAPHIC DATA

USED IN SELECTION OF REGIONS

Taxable Region Land Area Area Persons/ Pop per Median County Employment Sales Number (Acres) % of CA Population Acre Household Yrs School

Alameda 650,800 17,087,375 2 472,000 0.473% 1,375,900 2.915 2.710 13.9Alpine 450 18,861 4 472,740 0.474% 1,180 0.002 2.427 13.8Amador 12,490 254,562 4 379,240 0.380% 33,750 0.089 2.392 12.9Butte 75,500 1,598,552 5 1,049,340 1.051% 199,100 0.190 2.427 13.2Calaveras 12,830 176,520 4 652,920 0.654% 36,500 0.056 2.450 13.0Colusa 7,170 185,498 5 736,500 0.738% 18,300 0.025 2.876 12.5Contra Costa 435,500 8,575,704 2 460,980 0.462% 879,200 1.907 2.668 14.3Del Norte 9,230 145,303 1 645,050 0.646% 28,250 0.044 2.626 12.7El Dorado 69,300 979,382 4 1,095,350 1.097% 142,200 0.130 2.624 13.6Fresno 326,300 6,552,968 5 3,816,450 3.823% 776,200 0.203 3.039 12.7Glenn 9,790 186,650 5 841,530 0.843% 26,800 0.032 2.788 12.6Humboldt 56,300 1,079,084 1 2,286,590 2.291% 126,600 0.055 2.434 13.3Imperial 40,700 1,012,588 3 2,672,030 2.677% 140,500 0.053 3.390 12.2Inyo 6,740 217,442 4 6,522,930 6.535% 18,350 0.003 2.272 12.8Kern 243,500 5,291,665 3 5,210,630 5.220% 628,200 0.121 2.919 12.7Kings 37,690 753,226 5 889,270 0.891% 118,200 0.133 3.232 12.5Lake 21,100 317,533 5 805,420 0.807% 54,800 0.068 2.340 12.7Lassen 10,540 200,359 4 2,916,790 2.922% 34,450 0.012 2.738 12.9Los Angeles 4,052,600 82,620,919 3 2,598,380 2.603% 9,488,200 3.652 3.038 13.0Madera 44,240 709,293 5 1,368,590 1.371% 111,600 0.082 2.972 12.5Marin 126,000 2,902,225 2 332,660 0.333% 242,200 0.728 2.411 15.4Mariposa 6,860 122,048 4 928,780 0.930% 16,000 0.017 2.368 13.0Mendocino 39,180 733,126 1 2,245,940 2.250% 85,900 0.038 2.534 13.0Merced 69,500 1,239,209 5 1,234,490 1.237% 201,000 0.163 3.150 12.6Modoc 3,720 60,059 4 2,524,390 2.529% 10,150 0.004 2.408 12.7Mono 5,490 136,774 4 1,948,470 1.952% 10,400 0.005 2.430 13.9Monterey 159,500 3,437,830 1 2,126,040 2.130% 371,500 0.175 3.088 13.2Napa 54,300 1,227,540 2 482,470 0.483% 120,800 0.250 2.592 13.6Nevada 37,970 705,378 4 612,900 0.614% 86,600 0.141 2.431 13.8Orange 1,288,700 32,533,206 3 505,400 0.506% 2,659,300 5.262 2.967 14.0Placer 98,400 2,783,550 5 898,820 0.900% 209,700 0.233 2.606 13.8Plumas 8,860 147,239 4 1,634,540 1.637% 20,350 0.012 2.208 13.0Riverside 567,400 11,138,861 3 4,613,220 4.621% 1,380,000 0.299 2.947 12.9Sacramento 513,900 11,980,275 5 618,040 0.619% 1,140,600 1.846 2.598 13.7San Benito 21,500 328,365 1 889,050 0.891% 44,350 0.050 3.161 12.7San Bernardino 645,100 13,126,523 3 12,839,540 12.862% 1,587,400 0.124 3.066 12.9San Diego 1,170,700 25,138,565 3 2,690,870 2.696% 2,724,400 1.012 2.777 13.8San Francisco 384,100 10,392,212 2 29,890 0.030% 778,100 26.032 2.441 14.2San Joaquin 213,800 4,422,080 5 895,640 0.897% 535,400 0.598 2.990 12.7San Luis Obispo 97,900 1,997,905 3 2,114,880 2.119% 234,100 0.111 2.530 13.7San Mateo 364,500 9,775,981 2 287,430 0.288% 701,100 2.439 2.774 14.2Santa Barbara 181,800 3,544,310 3 1,752,620 1.756% 398,000 0.227 2.829 13.8Santa Clara 864,300 25,260,854 2 826,380 0.828% 1,653,100 2.000 2.970 14.3Santa Cruz 128,600 2,087,730 1 285,310 0.286% 245,600 0.861 2.740 14.2Shasta 65,200 1,571,041 4 2,422,820 2.427% 162,700 0.067 2.483 13.0Sierra 1,560 23,301 4 610,200 0.611% 3,360 0.006 2.379 12.9Siskiyou 16,300 319,793 4 4,023,850 4.031% 44,400 0.011 2.338 12.9Solano 161,500 3,029,077 2 530,030 0.531% 375,400 0.708 2.930 13.5Sonoma 220,300 4,569,715 1 1,008,770 1.011% 426,900 0.423 2.561 13.9Stanislaus 169,000 3,772,868 5 956,520 0.958% 419,500 0.439 2.958 12.7Sutter 28,900 689,714 5 385,720 0.386% 74,700 0.194 2.695 12.9Tehama 20,840 391,669 5 1,888,670 1.892% 54,800 0.029 2.513 12.7Trinity 4,500 2,556,821 4 2,034,470 2.038% 13,400 0.007 2.394 12.8Tulare 135,100 371,102 5 3,087,570 3.093% 355,500 0.115 3.177 12.4Tuolumne 17,410 58,249 4 1,430,820 1.433% 52,100 0.036 2.396 12.9Ventura 354,800 6,544,583 3 1,181,410 1.184% 716,800 0.607 3.038 13.6Yolo 81,400 1,685,983 5 647,960 0.649% 154,500 0.238 2.646 13.8Yuba 18,200 326,204 5 403,490 0.404% 60,500 0.150 2.756 12.7Entire State 13,240,050 319,095,449 99,822,800 100.0% 32,609,000 0.33 2.882 13.4

California 1999 Statewide J - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

Civ Labor Unemploy Non-Ag Emp Per capita Income Manuf No. of Farm % Vehicles Pub RevCounty Force Rate % of CA income % of CA % of CA Farms of Land Reg pre cap per Capita

Alameda 684,800 5.0 4.84 $27,071 112.4 5.19 482 60.7 0.57 $113Alpine 500 9.7 0.05 $22,105 91.8 0.05 Note 1 Note 1 0.74 $1,632Amador 13,370 6.6 0.10 $18,761 77.9 0.05 367 62.3 0.64 $263Butte 82,900 9 0.50 $18,040 74.9 0.20 1,944 43.1 0.52 $108Calaveras 14,130 9.2 0.10 $17,973 74.6 2.30 438 37.7 0.70 $196Colusa 8,860 19.1 0.05 $19,799 82.2 Note 1 836 61.1 0.51 $284Contra Costa 458,100 4.9 2.30 $31,246 129.7 1.90 675 35.4 0.62 $121Del Norte 10,270 10.2 0.10 $14,935 62.0 0.05 86 2.0 0.47 $148El Dorado 73,900 6.3 0.30 $23,161 96.1 0.10 690 9.3 0.61 $214Fresno 375,000 13 1.90 $18,329 76.1 1.20 7,021 46.5 0.45 $89Glenn 11,510 14.9 0.05 $15,866 65.9 0.05 1,187 56.3 0.48 $115Humboldt 60,900 7.5 0.40 $18,917 78.5 0.40 874 26.1 0.54 $154Imperial 57,700 29.4 0.30 $14,790 61.4 0.10 657 19.9 0.51 $105Inyo 7,360 8.4 0.10 $20,645 85.7 Note 1 79 0.1 0.64 $544Kern 279,000 12.7 1.40 $17,625 73.2 0.70 1,995 54.5 0.44 $190Kings 43,300 12.9 0.20 $13,982 58.0 0.20 1,092 87.2 0.39 $134Lake 23,820 11.4 0.10 $19,060 79.1 Note 1 815 20.4 0.66 $187Lassen 11,800 10.6 0.10 $16,058 66.7 0.05 312 16.7 0.43 $127Los Angeles 4,415,500 8.2 29.80 $23,501 97.6 31.50 1,446 7.1 0.52 $137Madera 51,530 14.1 0.20 $15,842 65.8 0.20 1,709 54.8 0.45 $152Marin 130,400 3.4 0.80 $43,318 179.8 0.20 260 50.8 0.71 $234Mariposa 7,520 8.8 0.05 $18,255 75.8 Note 1 256 22.2 0.66 $573Mendocino 42,780 8.4 0.20 $19,673 81.7 0.20 1,088 32.3 0.57 $265Merced 82,900 16.2 0.40 $15,653 65.0 0.30 2,879 79.2 0.44 $114Modoc 4,220 11.8 0.05 $15,519 64.4 Note 1 466 27.2 0.47 $272Mono 6,140 10.5 0.05 $20,084 83.4 Note 1 73 5.3 0.64 $698Monterey 179,300 11 0.90 $25,270 104.9 0.50 1,245 64.6 0.52 $147Napa 57,800 6 1.10 $27,881 115.7 0.40 1,227 48.8 0.60 $226Nevada 40,730 6.8 0.20 $20,917 86.8 0.10 415 11.8 0.63 $161Orange 1,343,900 4.1 9.30 $27,420 113.8 10.70 379 12.0 0.59 $48Placer 104,100 5.4 0.60 $25,933 107.7 0.60 1,125 15.3 0.64 $243Plumas 10,050 11.9 0.10 $19,844 82.4 0.05 125 7.3 0.68 $352Riverside 618,000 8.2 2.70 $19,632 81.5 1.70 3,511 9.2 0.48 $121Sacramento 546,900 6 3.80 $23,038 95.6 1.30 1,427 61.3 0.54 $196San Benito 24,400 11.9 0.10 $18,266 75.8 0.10 611 67.5 0.50 $147San Bernardino 695,100 7.2 3.60 $17,848 74.1 2.40 1,653 10.0 0.48 $75San Diego 1,236,300 5.3 7.80 $23,263 96.6 4.40 6,565 19.2 0.55 $96San Francisco 403,000 4.7 4.20 $36,061 149.7 2.10 Note 1 Note 1 0.44 $1,300San Joaquin 240,800 11.2 1.30 $18,874 78.3 1.50 4,097 87.5 0.47 $141San Luis Obispo 103,600 5.5 0.60 $20,490 85.1 0.20 1,880 62.6 0.59 $237San Mateo 377,200 3.4 2.50 $35,802 148.6 2.40 302 20.0 0.75 $163Santa Barbara 192,700 5.7 1.10 $25,860 107.3 0.90 1,613 47.8 0.54 $178Santa Clara 896,600 3.6 6.90 $31,487 130.7 19.10 1,057 41.5 0.63 $127Santa Cruz 140,200 8.3 0.70 $26,202 108.8 0.90 771 18.5 0.57 $184Shasta 72,300 9.9 0.40 $19,558 81.2 0.20 844 16.0 0.54 $108Sierra 1,750 10.9 0.05 $19,176 79.6 Note 1 53 9.1 0.63 $728Siskiyou 18,820 13.4 0.10 $17,853 74.1 0.10 689 16.1 0.61 $165Solano 174,700 7.6 1.10 $21,873 90.8 0.70 850 64.2 0.53 $97Sonoma 230,400 4.4 1.20 $25,888 107.5 0.90 2,737 51.3 0.61 $175Stanislaus 196,600 14 1.00 $18,122 75.2 1.70 4,354 79.4 0.49 $94Sutter 34,300 15.7 0.30 $19,767 82.1 0.10 1,362 82.5 0.52 $133Tehama 23,260 10.4 0.10 $15,154 62.9 0.10 1,381 53.8 0.47 $146Trinity 5,250 14.2 0.05 $15,877 65.9 Note 1 113 5.7 0.60 $288Tulare 160,600 15.9 0.70 $16,144 67.0 0.60 5,469 43.9 0.42 $135Tuolumne 19,390 10.2 0.10 $18,214 75.6 0.10 249 9.6 0.63 $270Ventura 381,800 7.1 1.90 $24,736 102.7 2.20 2,195 27.1 0.59 $118Yolo 86,900 6.3 0.60 $22,093 91.7 0.40 912 80.1 0.51 $77Yuba 21,100 13.9 0.30 $14,532 60.3 0.05 719 58.2 0.47 $119Entire State 15,596,100 7.2 $24,090 77,657 29.0 0.55 $124 Note 1: These entries had no value shown in the original data, indicating that they were zero.

California 1999 Statewide J - 2 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

APPENDIX K: QUESTIONS USED TO

DETERMINE SUITABILITY OF SORTING

SITES

1. GENERAL INFORMATION TO PROVIDE TO SITE

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•

•

•

•

Thank you for agreeing to help out with the statewide study.

We’ll be conducting the study in July and August.

We will need 6 samples from residential packer trucks (pure residential loads as much as possible) and 10 samples from self-haul loads. Samples will be collected all on one day and most likely sorted that same day – in unusual circumstances, we may need to finish sorting on a second day.

For generator sites, we will also be collecting samples directly from businesses in the area and bringing them to your site for sorting and disposal. This sampling will require an additional 3 to 10 days at your site.

We will also be conducting a gate survey to determine the percentage of waste at your facility from residential, commercial, and self-haul sources. This survey will be done for 1 day – the same day we collect the residential and self-haul samples.

2. CONTACT INFORMATION

Name of site

Date

Physical Address

City

Zip

Site Owner/ Operator Person approving use of the site Email

Address

City

Zip

Phone

Fax

Site Manager

Email

Address

City

Zip

Phone

Fax

Person with data about the site Email Address

City

Zip

Phone

Fax

California 1999 Statewide K - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

Who should the sampling crew and gate surveyor contact when they come on-site? Will they be available in July/August? Yes No If they are on vacation or not there, who do we see? _______________________________________________________________________ 3. SITE TRAFFIC INFORMATION Does the site receive: A) Residential packer loads? Yes No Do you know if there are pure residential loads coming in? Yes No Don’t Know Do they come in any particular day or time? B) Commercial packer loads? C) Self-haul loads? Both from residential sources and non-residential sources (like

landscaping, construction)? Do they come in any particular day or time? Facility’s hours of operation: M ____________ T ____________ W ____________ Th ____________ F ____________ Sat ____________ Sun____________ Do you close early if you have reached your allowed daily tonnage amount? Yes No Does this happen very often? Yes No Are there site conditions we need to be aware of such as high winds, snakes or other

animals, other special circumstances? What are your peak traffic times for: Residential packers____________ Commercial packers____________ Self-haul residential____________ Self-haul commercial____________


Would it be possible for the sorting crew to be there when the site is closed, for example

after hours or on weekends if needed? Yes No How many scales do you have? Do different types of trucks go to different scales (i.e., all self-haul going to one scale?) How is traffic handled at the gate? (in relation to how we can select vehicle loads for sorting) Is any recycling or recovery done at the site? If yes, what materials? And how is it done? How are loads directed to recycling areas/how are recyclers handled? The purpose of the study is to characterize disposed wastes only. If materials are

recovered, we need to sample what is left. What is the best way to do this at your site? We need to know how many loads of different types of waste you receive. Can you give this

to me now, or should I fax you a short form to fill out?

Number of Loads

Day of Week Single Fam. Res.

Comm. Packer

Comm. Roll-off

Transfer Truck

Self Haul Pickup or Smaller

Self-Haul Bigger Than Pickup

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Any waste streams/types the facility does not accept that we need to sample? Are there size restrictions on loads? _______________________________________________________________________ 4. SAMPLING RESIDENTIAL AND SELF-HAUL LOADS AT YOUR SITE Crews have hardhats, orange vests, coveralls, boots, gloves. Any other safety equipment or

special procedures you want them to use?


We need an area for the sorting crew to work, for the entire time we will be at the site. It needs to meet the following criteria (check box if yes/okay):

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•

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Size of about 2 parking spaces

It should be convenient to the disposal point, but not interfere with your operations. Or, samples from the loads need to be moved to the sorting area.

We also need a space near the pit or disposal face for residuals after sorting is complete. We will dispose of the residue from the sorting where you request at the landfill face or in the transfer station pit.

Is it possible to get a sheltered site, or to allow the crew to set up a shelter (like a canopy)?

Is it okay to have the crew there on weekend days? Can you provide a loader and operator in the tipping area to pull samples from the selected

loads? Yes No We need access to the load for enough time to collect the sample. The sort crew will

designate where to collect the sample in the pile and guide the operator to drop the sample. We expect that it will take from two to five minutes to obtain a sample. Is this okay?

Yes No If no loader available, can we manually collect the samples from the pile, which will take a

little longer? Yes No Loads will be randomly chosen throughout the day for sampling (6 residential packers, 10

self-haulers). Vehicles will be selected at the gate for sampling, and we will need a net weight of these vehicles. Vehicle selection will involve marking down the number of the selected vehicles as they pass through the gate and giving a card to selected vehicles. The vehicle will be directed to dump the load in an area where the sample can be pulled.

Is a person available at the gatehouse to help select vehicles for the 1 day? Yes No _______________________________________________________________________


5. ADDITIONAL INFO FOR GENERATOR SAMPLING SITES We will also be collecting samples directly from businesses in the area. The sampling crew

will be collecting the samples and delivering them to the site for the sorting crew to sort. Between approximately 30 and 100 samples of about 125 lb each will be brought to your site to be sorted and ultimately disposed. Therefore we will need to be at your site an additional 3 to 10 days. Samples will be the same type of waste accepted by your facility, but may come from areas not normally disposing at your facility (i.e., from counties or cities not normally in your area). Is this okay?

Yes No Do special arrangements need to be made? Do we need to contact local haulers about this? Generator samples may need to be stored overnight – collected one day, sorted the next.

Need space and need to meet permit conditions. Is this okay? Yes No _______________________________________________________________________ 6. GATE SURVEY INFO On the one day that we are taking samples of waste from vehicles entering your site, we will

also be surveying all vehicles entering the site during an 8 hour survey period. We will need net weights of all vehicles surveyed and vehicles chosen for sampling. Will be doing a short interview of drivers of all vehicles, commercial haulers and self-haulers, to determine whether load is residential, commercial, or from one of 5 self-haul categories. Depending on how busy your site is, we will use one or two surveyors. The surveyors will bypass vehicles if they are impeding the flow of traffic into the site.

Can you provide vehicle counts during the survey period? What safety equipment is needed by gate surveyor? What types of vehicles are not weighed? Are they charged a minimum fee? Yes No How is tonnage estimated for these loads? Are there any potential problems with recording the weights of all vehicles that enter the site

for the survey? 7. FINAL LOGISTICS Can you please send me

•

•

Written directions to the site(such as used for directing tour groups)

Plan of area where we could sample (taken from permit) Please remember to notify gate personnel.


Any other special circumstances we need to be aware of? Anything you need from us? Your main contact will be me – give your name and phone number. The contact for the field

crew is Brad Anderson of Sky Valley Associates. CIWMB will be sending you a confirmation letter. We will also cc your LEA in that letter and

notify the Board’s Permitting and Enforcement staff, just so they are aware that you are cooperating with the Board’s project.

As we get closer to the study period, we’ll arrange specific days for the crew to be at your

site. We will send you a reminder letter 2 weeks before we will be at your site, and remind you again a few days before the crew will be there.

The CIWMB may wish to set up site visits during sorting for Board staff to observe field work

for the project. Is this okay? Yes No We will let you know ahead of time about this. Do you mind if we put info on the Board’s LEA web site that you are participating in the

study? Yes No We may need to contact you again for more detailed info for gate survey – person

contacting you will be ____________ from Cascadia. Do you have any other questions? Thank you for your time today, and thank you for helping us out with this important study.


APPENDIX L: DATA ELEMENTS OF THE

STUDY

This section lists the pieces of information collected during the course of the study. Each datum was used either in planning the waste sampling process or in conducting the analysis. Vehicle surveys

Date of survey

Location (site) of survey

Minimum weight at that site

Surveyor name

Page number + line number to uniquely identify each record

Vehicle license number or vehicle ID

Substream (SH, SF res, MF res, Com, or mixed res & com)

If mixed res & com, then ask driver to estimate percentage of each to total 100%

If SH, then determine activity that generated the waste: SF residential, MF residential, C&D, roofing, landscaping, or commercial/industrial/institutional/other

Net weight of load, specifying units as tons, pounds, or cubic yards

Misc. field notes

California 1999 Statewide L - 1 Cascadia Consulting Group, Inc., for the Waste Composition Study California Integrated Waste Management Board

Composition database, containing records from disposal site samples and generator samples

Date of sampling

Site

Sample number (unique for each sample)

Substream:

Residential

Single-Family

Multi-Family

Commercial

Self-Haul

Residential

Commercial/industrial/institutional/other

Roofing

Landscaping

C&D

Business name (generator only)

Business/Multi-family ID number (generator only)

Business SIC grouping (generator only)

Business Tier grouping (generator only)

Business number of employees on site

Total volume of dumpsters (generator only)

How full are dumpsters when sampled? (generator only)

Weight of one cubic yard of waste (generator only)

Weight of each material or RPPC

City or district where load originated (res & SH only)

Vehicle type (res & SH only)

Vehicle license number (res & SH only)


Information for Vehicle Selection

Number of single-family residential packers at site per day

Number of commercial-hauling vehicles at site per day

packers

roll-offs

Number of self-haul vehicles at site per day (not broken down by size)


statewide waste characterization study

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